Meetings/Workshops on Neural Networks and Artificial Intelligence, Machine Learning in Canada

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

Phonetics is the study of the sounds of the worlds languages and how they are used to communicate. A wealth of information is known by linguists about which sounds are used, how they are produced, how children learn these sounds, and how the use of sounds differs between different groups of speakers. Still, many fundamental questions remain unanswered relating to this important part of human language. The purpose of this Focussed Research Group is to bring together mathematicians and computer scientists who are interested in phonetics with linguists who are seeking ways to i) handle the massive amounts of data that are available in the human speech stream, and ii) develop mathematical models to clarify research questions and guide empirical study.

Modeling and Simulation,    Natural Language Processing, Computational Linguistics

Optimal transport has now become an integral part of models for important tasks in machine learning, including deep learning and domain transfer. Recently, analytical approaches have shown to provide important information about the behavior of the functions that model key tasks in machine learning, including their asymptotics and stability, as well as their numerical optimization. The aim of the workshop is to bring together experts, as well as young researchers, in optimal transportation, applied analysis, scientific computing, and machine learning, to consider some of the interesting and deep research questions that would benefit from joint expertise.

Understanding the relationship between structure, dynamics, and function in the brain is a crucial step toward innovative solutions for brain-related diseases such as epilepsy, Parkinson’s disease and Autism Spectrum Disorders, and hence, it is of immense importance for society. Complex network approaches have successfully provided new insights about the structure and function of the brain for two decades. With recent advances in data science for neuroscience, the increased complexity of the data such as neurosignals from multiple frequency bands, large-scale optical imaging of neuronal activity, and high-resolution Functional Magnetic Resonance Imaging, has led to the proposition that multilayer-network models are essential to model and understand brain dynamics. This workshop builds on early successes using this framework and brings together a diverse group of world-leading experts of various backgrounds to take the application of multiplex networks in neuroscience to the next level. Bridging the gap between complex network theory and neuroscience. We expect that this workshop and the transdisciplinary collaborations between the different fields and participants will stimulate significant advances in our understanding of the brain and indeed lead to new diagnostic methods and treatments of brain related diseases in the future.

Human epilepsy is a common neurological disorder, 0.6% of Canadian suffer from it. The focus of this 2-days meeting is mathematical processing of epilepsy-associated EEG data, its role in seizure analysis and diagnostics. The purpose is to bring together three groups of researchers: physicians specializing in drug-resistant epilepsy, behavioral neuroscientists, and applied mathematicians.Thanks to the first group, extensive clinical data is available with detailed description. The second group experiments with animals, and some data analysis methods can be applied to clinical data as well. This is a conference, a brainstorming activity and a training opportunity for research associates, postdoctoral fellows and graduate students involved in all three groups. The proposed participants are members of the mathematics and statistics departments, neurology, clinical neurosciences, cell biology, physiology, psychology and practicing medical doctors.

The MIDL conference aims to be a forum for deep learning researchers, clinicians and health-care companies to take a leap in the application of deep learning based automatic image analysis in disease screening, diagnosis, prognosis, treatment selection and treatment monitoring. The conference will have a broad scope and include topics such as computer-aided screening and diagnosis, detection, segmentation, (multi-modal) registration, image reconstruction and synthesis.

Pattern Recognition and Image Processing, Machine Vision,    Radiology (in general)

UAI is supported by the Association for Uncertainty in Artificial Intelligence (AUAI).

The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty.

Strategy Institute

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