Konferenzen  >  Mathematik  >  Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen

Algorithmen und Datenstrukturen,    Implementierung und Anwendungen von künstlicher Intelligenz

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Wissenschaftliches Rechnen und Datenwissenschaft,    Informations & Wissensmanagement, Big Data Computing

6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances.

Email: cmla@cseit2024.org

Bayesian Network Computer Vision Data Mining Deep Learning Learning in knowledge-intensive systems Learning Methods and analysis Learning Problems Machine Learning Algorithms Neural Networks Predictive Learning Reinforcement Learning Supervised Machine Learning Unsupervised Machine Learning

Mustererkennung und Bildverarbeitung, Maschinelles Sehen,    Implementierung und Anwendungen von künstlicher Intelligenz

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

This seminar aims at reasoning critically about how we build software and hardware for end-to-end machine learning. We hope that the discussions will lead to increased awareness for understanding the utilization of modern hardware and kickstart future developments to minimize hardware underutilization. We thus would like to bring together academics and industry across fields of data management, machine learning, systems, and computer architecture covering expertise of algorithmic optimizations in machine learning, job scheduling and resource management in distributed computing, parallel computing, and data management and processing. The outcome of the discussions in the seminar will therefore also positively impact the research groups and companies that rely on machine learning.

International Association of Computer Science and Information Technology

The 7th International Conference on Machine Learning and Machine Intelligence (MLMI 2024) will be held in Osaka, Japan during August 2-4, 2024. MLMI 2024 is organized by Ritsumeikan University, Japan.

Email: aimee@iacsit.net

Artificial Neural Networks; Genetic Algorithms; Association Rule Learning; Inductive Logic Programming; Automata, Logic and Games; Intelligent Systems; Machine Learning;

International Association of Computer Science and Information Technology

The 2nd International Conference on Machine Learning and Pattern Recognition (MLPR 2024) will be held in Osaka, Japan during August 2-4, 2024. MLPR 2024 is organized by Ritsumeikan University, Japan.

Email: aimee@iacsit.net

Machine Learning; Active learning; Pattern Recognition; Analysis and detection of singularities; Animation image analysis;

Ai4

Over two and a half days, join thousands of executives and technology innovators at the epicenter of the AI community. Discover the latest applications, advancements, and best practices shaping the future of AI. Enjoy dedicated content & unbeatable networking for both business & technical leaders from every major industry and job function, from leading AI startups, investors, and government organizations.

Email: info@ai4conferences.com

artificial intelligence, AI, machine learning, innovation, startup, AI Ethics, AI governance, AI transformation, data, data strategy, generative AI, Productivity Tools, Machine Learning, NLP, Computer Vision, Neural Networks, Education, Finance, Financial Services, Government, Healthcare, Technology, Tech, Manufacturing, Retail, Cyber, Cybersecurity, Data Analytics, Data Engineering, Data Science, Marketing, CX, Advertising, Sales, AI Research, Blockchain, Generative Models, ML Ops, Recommender Systems

Punjab Engineering College, Chandigarh and IEEE Chandigarh Subsection

INDISCON is a flagship annual international conference of the IEEE India Council organized by an IEEE Subsection in INDIA. INDISCON 2024 scheduled during August 22-24, 2024, is being organized by IEEE Chandigarh Subsection along with IEEE India Council. The conference will be hosted by Punjab Engineering College (Deemed to be University), Chandigarh. The conference aims to provide an interdisciplinary platform for the academicians, researchers, industry professionals and research scholars to exchange and share their knowledge, experience & research. Papers that are selected and presented at the conference will be submitted to IEEE Xplore.

INDISCON;     Tel.: [+91-9417429699];     Email: ieeeindiscon2024@gmail.com

Power and Energy Systems, Power Electronics, Drives and Intelligent Control, Instrumentation, Control and Signal Processing, Artificial Intelligence and Data Science, Communication, Networks & IoT, Next Generation Computing and Applications, Security & Privacy, RF/Microwave/Terahertz Technologies, Semiconductor Devices, VLSI & Embedded Systems, Nanotechnology Materials and Devices, Education Technologies, Women in Engineering

Elektrotechnik,    Elektronik

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

AI is a disruptive force. With growing applications in fields like healthcare, transportation, game playing, finance, or robotics in general, AI systems and methods are entering our everyday lives. Such tight interaction with AI requires serious safety, correctness, and reliability considerations. Recently, the field of safety in AI has triggered a vast amount of research. Via a diverse program with ample space for open yet guided discussion, we aim to address a number of key challenges that range across all fields.

Institute of Mathematics and its Applications

Join us at the forefront of innovation! The Institute of Mathematics and its Applications is proud to present the AI/ML Congress 2024—an inclusive gathering of academics, industrialists, and AI enthusiasts from diverse fields. Explore the limitless possibilities of Artificial Intelligence and Machine Learning through engaging presentations, panel discussions, and unparalleled networking opportunities.

Conference Office;     Email: conferences@ima.org.uk

Artificial Intelligence, Machine Learning, Healthcare, Finance, Environment, Manufacturing, Retail, Legal, Media

Open Data Science Conference

ODSC Mini-Bootcamp is coming back to London this September. Learn in 3 Days -What Other Bootcamps Take Months to Teach.

Email: iryna@odsc.com

Bootcamp, Data Science, Machine Learning

TOBB Economics and Technology University

ATSF is an international conference series organized to bring together researchers from ALL areas of Approximation Theory and Special Functions to discuss new ideas and new applications. This organization, which has been held seven times so far as mini-symposia, has grown gradually over the years and will be held for the eighth time on September 4-7, 2024, hosted by TOBB Economics and Technology University (Ankara, Türkiye).

Conference Chair;     Email: atsf2024@gmail.com

Approximation Theory, Summability Theory, Applied Mathematics, Special Functions; Analysis and Functions Theory

Angewandte Mathematik (allgem.),    Analysis

ODSC Europe will be as inclusive as we have demonstrated before — from in-person sessions to digital experiences available to everyone, from anywhere. Get ready for the in-person and virtual ODSC Europe conference. Combining small immersive in-person sessions and hands-on training with innovative and insightful virtual ones — it’s going to be one fantastic event to RECONNECT!

Email: iryna@odsc.com

Data Science, Artificial Intelligence, LLMs, Generative AI

University of Johannesburg

AI technology is progressing worldwide. The aim of the interdisciplinary conference is to analyse and evaluate the economic drivers and consequences of the diffusion of AI for companies, users, and society. The conference offers various tracks and opportunities for exchange and discussion. Accepted, presented, and revised contributions will be published in the conference proceedings.

Email: info@epe.ai

artificial intelligence, microeconomic, macroeconomic, entrepreneurship, digital transformation, business administration, finance, accounting, controlling, human resources, marketing, production, quality management

China Communications Information & Technology Group Co., Ltd., Beijing Institute of Control Robotics and Intelligent Technology, Beijing University of Chemical Technology, Xi'an Jiaotong University, Deakin University

2024 The 3rd International Conference on Artificial Intelligence and Blockchain Technology (AIBT2024) will be held in Beijing, China during September 14-16, 2024 as the workshop of BDIOT 2024.

Email: emmaawang2019@sina.com

Artificial Intelligence; Evaluation of Al tools; Blockchain; Application of digital currency; Blockchain investment; Blockchain landing application;

The Hausdorff Research Institute for Mathematics (HIM)

The interaction between learning theory and harmonic analysis was emphasized by mathematics of quantum computing. One of the outstanding open problems in this area concerns the sharp estimates in Bohnenblust-Hille inequality that generalizes a celebrated Littlewood’s lemma. How to learn (with small error and with large probability) a complicated function or a very large matrix in a relatively small number of random (quantum) queries? Of course, there should be some Fourier type restrictions on a function (a matrix) to have a reasonable answer to this. The “classical” way of learning (Boolean) functions comes from very sophisticated extensions of theorems of Kahn—Kalai—Linial type. In those results the interplay between maximal influence and heavy Fourier tails is the main technique. Maximal influence should be large if the `tail’ is small. However, recently another approach that is hinged on Bohnenblust—Hille inequality appeared. The school will cover the classical maximal influence approach to `probably approximately correct' (PAC) learning as well as the recent achievements using Bohnenblust—Hille inequality and its quantum counterpart.

Analysis,    Kurse und Veranstaltungen für Studenten der Mathematik

AIPR2024 is mainly organised by Huaqiao University, co-sponsored by Wuhan Institute of Technology and Minnan Normal University, China.

Today, AI is surrounding us, it is coordinated into our every day lives. Artificial Intelligence is empowering machines to behave like humans by adding Emotional Quotient(EQ) to them. Artificial intelligence is a blooming technological advancement, from software’s like Alexa, to basic human command system. Big data can be used to speed up AI development and soon AI will significantly impact our everyday lives. AI is the future and it’s here to stay. In the future, there will be a greater demand for people who can program machines to “think” and enrich human lives. A pattern is a short description of the data. Pattern recognition is how agents make predictions, which is a central problem in AI. Pattern recognition forms the basis of learning and action for all living things in nature. The importance of Pattern Recognition can be traced from its needs in daily life- pattern recognition plays an important role: reading texts, identifying people, retrieving objects, or finding the way in a city. Once patterns are established, learned from some examples or from a teacher, we are able to classify new objects or phenomena into a class of known patterns. Pattern Recognition is a vast area of research and there are endless number of possibilities as pattern recognition is still under research as it is getting more futuristic and intelligent with a great affect in human life in a positive manner.

Email: Dunn@iact.net

Pattern Recognition and Machine Learning; Computer Vision and Robot Vision; Image, Speech, Signal and Video Processing; Document Analysis, Biometrics and Pattern Recognition Applications; Biomedical Image Analysis and Applications;

International Academy of Computing Technology

2024 7th International Conference on Big Data and Machine Learning will be held in Xiamen, China during September 20-22, 2024. Machine Learning (ML) and Big Data Processing & Analytics (BDA) are both evolutionary fields of computing and the developments in these fields are complementing each other. The ever changing data landscape in modern digital world have resulted in newer ways of data processing frameworks in order to get meaningful insights which are unprecedented. ML based Big Data Processing has gained popularity and new developments are on the rise for efficient data processing. This field is witnessing unparalleled emergence of new methods and approaches for efficient data processing in order to discover interestingness for decision making. Thus, more and more ML based data processing approaches are being used for Big Data Processing. With the splurge data from different newer sources, heterogeneous nature of data, uncertain & unstructured data, the so called Big Data with all its characteristics (5 Vs) there is an ever increasing need to use approaches which aid in modelling and processing of these data, provide automated approach to data processing and so on. Thus the BDML conference series welcomes the scholars who are researching in this interesting & challenging domain of ML and Big Data Processing and provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Big Data and Machine Learning.

Email: Dunn@iact.net

Big Data; Machine learning;

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Institute 2024 has an overarching focus on Next-Generation Human-Centred AI and Cognitive Technologies; its technical programme addresses the formal & cognitive foundations for human-centred computing (for AI), and the human-centred design, development, and usability of cognitive technologies aimed at human-in-the-loop assistance & empowerment in decision-making, planning, creative-technical problem-solving, and automation. Application areas to be addressed in the institute include autonomous vehicles, cognitive robotics, social robotics, cognitive/creative design assistance technologies (e.g., architecture and built environment design, visuo-auditory narrative media design), clinical diagnostics, technology-assisted education/learning.

MODE (for Machine-learning Optimized Design of Experiments) is a collaboration of physicists and computer scientists who target the use of differentiable programming in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection. Our aim to develop modular, customizable, and scalable, fully differentiable pipelines for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.

Wissenschaftliches Rechnen und Datenwissenschaft,    Computerphysik und Numerische Simulation

Institute for Pure and Applied Mathematics (IPAM), UCLA

The study of biological intelligences has been transformed by breakthroughs in experimental and observational methods. New data have expanded our appreciation of the sophisticated behaviors exhibited by human and non-human animals across a range of taxa. Traces of intelligent behavior are typically high-dimensional, with complex structure in space and time. They often involve multiple data streams: for example, positional information from individual members of a bird flock, as well as “point-of-view” recordings showing what birds are looking at, moment by moment; or electrocorticographic recordings of human brain activity, as well as detailed traces of motor behavior. These traces are often buried beneath complex noise environments: individual animal movements must be pulled out of extensive visual clutter; whale song must be isolated from ocean noise. This complex, high-dimensional data requires entirely new approaches to data representation, integration, and analysis. This workshop will focus on the challenges raised by high-throughput, high-dimensional studies of intelligent behavior. It will bring together experts in animal cognition, computational neuroscience, and cognitive science with mathematicians and computer scientists focused on relevant methods in machine learning, network science, high-dimensional statistics, and information theory.

Part of the Long Program Mathematics of Intelligences

American University in the Emirates

The Artificial intelligence conference aims to delve into the latest trends, ideas, and practices within these dynamic and interconnected fields. Artificial intelligence has emerged as a transformative technology, revolutionizing industries, and reshaping our world. From self-driving cars to virtual assistants, AI has permeated various aspects of our lives, presenting both new opportunities and challenges

Machine Learning Deep Learning Neural Networks Future of AI Natural Language Processing (NLP) Computer Vision Robotics Data Mining Predictive Analytics Cognitive Computing Expert Systems Reinforcement Learning Speech Recognition Image Recognition Virtual Assistants Big Data Decision Trees Genetic Algorithms Chatbots Autonomous Vehicles Pattern Recognition

5th International Conference on Artificial Intelligence and Machine Learning (CAIML 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.

Artificial Intelligence AI Algorithms Artificial Intelligence Tools and Application Automatic Control Bioinformatics CAD Design and Testing Computational Theories of Learning Computer Vision and Speech Understanding Data Mining and Machine Learning Tools Fuzzy Logic Heuristic and AI Planning Strategies and Tools Hybrid Intelligent Systems Information Retrieval Intelligent System Architecture Knowledge Representation Knowledge-based Systems Mechatronics Multimedia & Cognitive Informatics Natural Language Processing Neural Networks Parallel Processing Pattern Recognition Pervasive Computing and Ambient Intelligence Programming Languages Reasoning and Evolution Recent Trends and Developments Robotics Semantic Web Techniques and Technologies Soft computing theory and Applications Software & Hardware Architectures Web Intelligence Applications & Search Machine Learning Applications Learning in knowledge-intensive systems Learning Methods and analysis Learning Problems

Institute for Pure and Applied Mathematics (IPAM), UCLA

Neural networks have confounded traditional ML beliefs about the dangers of overfitting and the need for regularization. They have also given rise to many new empirical findings around transfer learning, adversarial examples, compressibility, scaling laws (relating the size of datasets, models, and compute), grokking, and so on. What is needed to explain and predict all this is a rich new theory of learning capable of addressing the delicate interplay between model, data, and optimizers at large scale. This workshop will bring together top researchers driving the frontiers of this work with experts in both theory and experiment for natural intelligence. The result will be a scholarly discussion on how to frame questions about learning and how to distill the similarities and differences between learning with biological and artificial systems.

Part of the Long Program Mathematics of Intelligences

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Kurse und Veranstaltungen für Studenten der Mathematik,    Implementierung und Anwendungen von künstlicher Intelligenz

ACMSC

2024 3rd International Conference on Artificial Intelligence and Software Engineering will be held in Singapore during October 25-27, 2024.

Email: amychou2020@163.com

Agent-based Systems; Agile Methodologies; AI for Software Engineering; Knowledge Engineering; Machine Learning; Middleware, Frameworks, and APIs;

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

The vision of NFDI4DS is to support all steps of the complex and interdisciplinary research data lifecycle in Data Science and Artificial Intelligence. The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artifacts available, interlinking them, and offering innovative tools and services. Within this Dagstuhl Research Meeting, the NFDI4DS partners will reflect on their progress so far, and will work on their long-term strategy.

Informations & Wissensmanagement, Big Data Computing,    Wissenschaftliches Rechnen und Datenwissenschaft

We are pleased to invite you to submit your full papers to the 3rd International Workshop on Artificial Intelligence for Natural Language Processing (IA&NLP’24) that will be held in conjunction with The 15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) October 28- 30, 2024, Leuven, Belgium.

AI, Natural Language Processing, NLP, artificial intelligence

Open Data Science Conference

This summit is co-located with ODSC West in the heart of Silicon Valley, brings together industry leaders and pioneers for two days of talks and panels on watershed technologies like Large Language Models, Generative AI, and more.

Email: iryna@odsc.com

AI, Data Science

Open Data Science Conference

Email: iryna@odsc.com

Data Science, Machine Learning, NLP, LLMs, LLama, Ollama

AI Media Group

AI Expo Africa 2024 is the largest artificial intelligence (AI), Intelligent Automation (IA) and smart tech trade event & conference in Africa. With a community of 50K+ business practitioners, the 7th Edition of AI Expo Africa will run 30-31st Oct 2024 in Johannesburg South Africa at the prestigious Sandton Convention Centre, uniting 1000s of decision makers, investors, buyers, suppliers, innovators, SMMEs and global brands focused on real world business applications you can deploy TODAY.

Event Manager;     Email: enquiries@aiexpoafrica.com

ML / DL / Gen AI Business Solutions RPA / Intelligent Automation / CX Chatbots / Conversational AI Big Data / Data Ops / Analytics Cloud / Data Centre / Storage / Super Computing ML Ops / Development Frameworks Security / DevSecOps IoT / 5G / Mobile / Edge Smart Devices / Hardware / Drones Autonomous Systems / Service Robots AR / VR / MR / Creative Media Training / Education & Skills Women & Youth in AI Applied University R&D AI4Good / Ethics / Privacy / Standards / Regulation & Policy Smart Cities / Smart Society & Smart Citizen National AI Strategies / Community Building

Implementierung und Anwendungen von künstlicher Intelligenz,    Internet der Dinge (IoT) und Sensornetze

Institute for Pure and Applied Mathematics (IPAM), UCLA

This workshop will draw together researchers creating new algorithms and architectures (e.g., active symbol architectures, evolutionary programming approaches, neural program synthesis) with mathematicians and theoretical computer scientists who specialize in non-convex optimization, the theory of programming languages, type theory, proof theory, and category theory. It aims to promote cross-fertilization between these paradigms and more traditional approaches, while stimulating the development of rigorous foundations for evolutionary computing, program synthesis, and other naturalistic approaches to AI.

Part of the Long Program Mathematics of Intelligences

Max Planck Institute for the Science of Light

In the "2nd Workshop on Machine Learning for Quantum Technology" we aim to attract researchers interested in the use of classical ML/AI techniques to advance the development of quantum technologies in a broad sense. Some examples would be analyzing quantum measurements, estimating the parameters of quantum devices, discovering new quantum experimental setups, protocols, and feedback strategies, and generally improving aspects of quantum computing, quantum communication, and quantum simulation. See the review paper here for more relevant topics. We will also cover some quantum machine learning topics and their interconnections with classical machine learning.

Quantenmechanik und Quantentechnologie,    Implementierung und Anwendungen von künstlicher Intelligenz

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Non-Bayesian approaches appear to solve many problems that Bayesians once dreamt of solving using Bayesian methods. We thus believe that it is timely and important to rethink and redefine the promises and challenges of Bayesian approaches; and also to elucidate which Bayesian methods might prevail against their non-Bayesian competitors; and finally identify key application areas where Bayes can shine.

Joint Research Center for Advanced and Fundamental Mathematics for Industry

Implementierung und Anwendungen von künstlicher Intelligenz,    Simulation

Central University of Punjab, Department of Mathematics and Statistics

The FIAM conference, organized by the Forum for Industrial and Applied Mathematics, serves as a premier platform for academia, researchers, and professionals to exchange insights and innovations in the field of mathematical sciences. Through national and international gatherings, FIAM fosters collaboration, showcasing advancements in data analysis, numerical methods, and simulation techniques. With a focus on real-world problem-solving, the conference bridges theory and practice, facilitating dialogue between academia and industry. By uniting diverse perspectives and expertise, FIAM conferences propel research forward, driving solutions to complex industrial challenges and advancing the frontiers of applied mathematics.

Convener;     Tel.: [+91-89686-44973];     Email: fiam.conf@cup.edu.in

Artificial Intelligence, Bio-Mathematics, Bio-Statistics, Boolean Functions and their Generalizations, Computational and Theoretical Fluid Dynamics, Computational Mechanics, Control and System Theory Cosmology and Celestial Mechanics, Cryptography, Differential Equations and Applications, Discrete Mathematics, Dynamical Systems and Nonlinear Analysis, Fractional Differential Equations, Fuzzy Systems, Geometry and Topology, Image and Signal Processing, Integral Equations, Mathematical Physics, Modelling and Simulation, Multimedia Security, Nano Fluid Mechanics, Neural Networks, Numerical Techniques, Operations Research, Probability and Statistics, Soft Computing, Soliton Solutions, Wavelet Analysis.

Angewandte Mathematik (allgem.),    Simulation

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Kurse und Veranstaltungen für Studenten der Mathematik,    Astronomie, Astrophysik und Kosmologie

Institute for Pure and Applied Mathematics (IPAM), UCLA

This workshop will bring together leading experts in the mathematical modeling of collective intelligence. While the workshop will explore collective intelligence in many different systems, substrates (both natural and artificial), and scales, it will focus on three broadly applicable modeling frameworks: dynamical systems, which have been applied to systems as various as brains and insect swarms; statistical physics, which has illuminated the behavior of flocking birds and deep learning architectures; and game theory, which has been applied to animal, human, and AI collectives. The collective intelligence domain cultivates the further development of formal tools for treating compositionality; the emergence of new capacities and collective degrees of freedom at multiple scales; and the higher-level institutions that coordinate the intelligent behavior of lower-level parts.

Part of the Long Program Mathematics of Intelligences

ETPUB

2024 11th International Conference on Soft Computing & Machine Intelligence will be held in Melbourne, Australia during November 22-23, 2024.

Email: helen@academic.net

Artificial Intelligence and Machine Learning; Data Mining and Knowledge Discovery; Probabilistic Reasoning and Uncertainty; Intelligent Control and Robotics; Computer Vision and Information Retrieval;

Quantum Techniques in Machine Learning (QTML) is an annual international conference focusing on the interdisciplinary field of quantum technology and machine learning. The goal of the conference is to gather leading academic researchers and industry players to interact through a series of scientific talks focussed on the interplay between machine learning and quantum physics.

Implementierung und Anwendungen von künstlicher Intelligenz,    Quanteninformationstheorie und Quanteninformatik

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

At the Dagstuhl Seminar on RNA Regulation and Multidimensional Transcriptomics, we will delve into the intersection of computational biology, deep learning, and RNA research. The event will explore how cutting-edge AI technologies are reshaping our understanding of RNA-based gene regulation and its role in health and disease.

Genomforschung und Bioinformatik,    Implementierung und Anwendungen von künstlicher Intelligenz

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Perspectives Workshop aims, first of all, to bring together the communities working on the related areas of learning through interaction, (conversational) agents in games, dialogue and interaction, and collecting judgments from crowds through games, to make each community aware of the most recent developments in the other areas. We also intend to discuss current challenges, and whether advances in one area (e.g., grounded interaction) can benefit other areas (e.g., interactive learning).

South American Institute for Fundamental Research (ICTP-SAIFR)

Kurse und Veranstaltungen für Physikstudenten,    Wissenschaftliches Rechnen und Datenwissenschaft

Scientific-Technical Union of Mechanical Engineering

The study of the processes in different real systems is limited to their modelling, i.e. their approximate description by creating models of these systems and processes. Systems and processes models are divided into two classes - physical and mathematical. In recent decades, it has become clear that the notion of mathematical modelling refers equally to systems of another nature - social, economic, and others. In other words, the behavior of different systems can be effectively explored using their mathematical models. It is only necessary to properly choose the appropriate mathematical apparatus. On the other hand, the range of mathematical models is extremely wide - from algebra and logic to functional analysis. This means that the regular direct contacts between engineer researchers and specialists from different fields of mathematics are very important for the advancement of science and technology. For professional mathematicians, these contacts will enable them to better target the needs of representatives of other areas of knowledge. And the more contacts there are the better. One of the most interesting problems of modern science is the development of methods and models for research and optimization of different systems. Thus knowledge is presented in a form that can be used. More and more mathematics is becoming the language of innovation and intelligent technologies and the modern industrial society.

Scientific-Technical Union of Mechanical Engineering;     Tel.: [(+359 2) 987 72 90];     Email: office@mathmodel.eu

Basic principles of mathematical modelling, Analogy principle, Model hierarchy, Methodology of mathematical modelling, System analysis, Mathematical modelling in fundamental and applied physics, mechanics, chemistry and biology, Technological processes as objects of automation, Mathematical methods of management, Modelling of smart production technologies and systems, Virtual technologies and simulations, Information and computer technologies, Robotics, Artificial intellect, Radio electronics, Statistical and stochastic models, Neural networks, Situation modelling,

Simulation,    Mathematische Logik, Grundlagen der Mathematik

AIGC 2024 will be a focal point for the latest advancements in Al-generated content. We believe this conference will provide a platform for participants to share cutting-edge information, ideas, and experiences in in Al-genelrated content and related fields. Your valuable contributions through papers and presentations,coupled with active participation, will undoubtedly enhance the overall success of the event.

Conference Secretariat;     Tel.: [+86-15618780723];     Email: contact@icaigc.org

T1: Foundations of AI Artificial General Intelligence Machine Learning Deep Learning Transformer Neural Networks T2: AI in Creative Expression Generative AI AI-generated Audio AI-generated Art AI-generated Image T3: Advanced AI Applications Natural Language Processing (NLP) Computer Vision Diffusion Models for Machine Learning AI in Robotics

CZESND

The 9th International Conference on Machine Learning and Soft Computing (ICMLSC 2025) will be held on January 24-26, 2025. The conference is organized by Chuo University, Japan, co-organized by Keiai University, Japan, and supported by University of Muenster, Germany and Concordia University, Canada.

Email: Nazal@sina.com

Machine learning; Intelligent planning; Visual/linguistic perception; Evolutionary and swarm algorithms; Neural computing; Emotional intelligence; Applications;

Softwareentwicklung,    Edge/Cloud-Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Artificial Intelligence, Computers and Society, Databases, Trust, Transparency, Accountability, Knowledge Graphs, Web Data

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

IEEE AIxVR stands out as a distinctive event that brings together researchers and professionals across the spectrum of Artificial Intelligence, Augmented Reality, Mixed Reality, and Virtual Reality. This event serves as a global platform fostering collaboration between these diverse fields, facilitating the presentation of cutting-edge advancements, identifying emerging research avenues, and collectively shaping the future of these dynamic research domains. We extend a warm invitation to researchers specializing in Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) to actively participate and contribute by submitting their work to the program. Moreover, we welcome submissions related to Artificial Intelligence (AI) that have a direct correlation to any of these immersive technologies or demonstrate potential applications within them.

Implementierung und Anwendungen von künstlicher Intelligenz,    Benutzerschnittstellen, User Experience, Virtuelle Realität

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Logic and learning are central to Computer Science, and in particular to AI-related research. Already Alan Turing envisioned in his 1950 “Computing Machinery and Intelligence” paper a combination of statistical (ab initio) machine learning and an “unemotional” symbolic language such as logic. The combination of logic and learning has received new impetus from the spectacular success of deep learning systems. The goal of this Dagstuhl Seminar is to bring together researchers from various communities related to utilizing logical constraints in deep learning and to create bridges between them via the exchange of ideas.

Implementierung und Anwendungen von künstlicher Intelligenz,    Informationstheorie und Grundlagen der Informatik

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In our daily lives, we as humans perceive our surroundings in an inherently multimodal way. Nevertheless, the vast majority of data analysis idioms are exclusively visual, not using the apparent potential of combined designs. While the visualization field studies visual data analysis solutions, the sonification field investigates comparable solutions that convey data over non-speech audio. There are several similarities between the methods and design theories of both approaches, such as the use of perceptual variables to encode data attributes, the use of marks and substrates for conveying items, and the role of interaction in manipulating the data representations. Over the recent decades, both fields have established research communities, theoretical frameworks, and toolkit support.

Implementierung und Anwendungen von künstlicher Intelligenz,    Mulitimedia und Computergrafik, Spiele

International Academy of Computing Technology

2025 9th International Conference on Digital Signal Processing (ICDSP 2025) will be held in Chengdu, China during February 21-23, 2025. It is Co-sponsored by Southwest Jiaotong University and Xihua University, China, and technically supported by many universities and institutions.

Email: Dunn@iact.net

MACHINE LEARNING AND STATISTICAL SIGNAL PROCESSING; DIGITAL AND MULTIRATE SIGNAL PROCESSING; DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS; SPEECH AND LANGUAGE PROCESSING; AUDIO AND ACOUSTIC SIGNAL PROCESSING;

Max Planck Institute for the Physics of Complex Systems (MPI-PKS)

Komplexe Systeme und Chaos ,    Quantenmaterialien, Tieftemperaturphysik

ACMSC

Email: amychou2020@163.com

Machine learning methods; Learning and adaptive control; Learning/adaption of recognition and perception; Learning for Handwriting Recognition; Learning in Image Pre-Processing and Segmentation; Learning in process automation; User experience research, usability testing and interaction design; Mobile, ubiquitous and pervasive computing; Technology adoption, trust, user engagement and retention;

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

International Association of Computer Science and Information Technology

The 7th International Conference on Computer Science and Technologies in Education (CSTE 2025) will be held in Wuhan, China during April 18-20, 2025. CSTE 2025 is sposored by Central China Normal University, China, hosted by Faculty of Artificial Intelligence in Education, Central China Normal University, China.

Email: aimee@iacsit.net

Educational Technologies and Systems; Computer-supported Collaborative Learning and Social Computing; Artificial Intelligence in Education; STEM Education and Computational Thinking; Educational Data Mining and Learning Analytics; Innovative Technologies for Teaching and Learning;

Informationstheorie und Grundlagen der Informatik,    Computergestütztes Lernen

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar will focus on bridging the gap between deep learning and knowledge graphs, and will discuss their integration: neurosymbolic AI. The aim is to advance the understanding of how symbolic knowledge - in the form of KGs - can be used to improve the capabilities of DL systems, and how DL can advance KG construction and applications.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

In a little over a year since the release of ChatGPT, language models (LMs) have stirred concerns in government, over the possibility that citizens will come to believe the textual and spoken output of such models. Similarly, they have caused panic in education, forcing a rethink of what students are learning and how to assess it. Of concern to us here, is whether LMs mean the end of computational and/or cognitive models of human language learning and language use. Does the practical success of LMs mean that computational linguistics (and perhaps even linguistics itself) is no longer relevant? Or are we missing problems with LMs that computational linguistics (and linguistics more generally) could help us both recognize and surmount?

Implementierung und Anwendungen von künstlicher Intelligenz,    Verarbeitung Natürlicher Sprache, Computerlinguistik

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

This Dagstuhl Seminar aims to bring together experts and stakeholders in Generative AI and computing education to foster collaboration and to chart a way forward as Generative AI continues to improve and proliferate. It is the goal of this seminar to leverage the experience and knowledge of dozens of programming education experts from around the world to form an enduring community of practice. During the Dagstuhl Seminar, we intend to develop strategies for incorporating LLMs into programming education and to rigorously evaluate their use and impact. This seminar will explore the following topics in the context of Generative AI in programming education: accessibility; diversity, equality, and inclusion; resources; introductory programming for computer science majors and non-majors; advanced courses (that use programming); curriculum changes; novel pedagogies, approaches and tools; and industry use and changes that may lead to new learning outcomes.

Computergestütztes Lernen,    Didaktik in der Wissenschaft

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Geometrie und Topologie,    Optimierungsrechnung, Entscheidungsunterstützung