Konferenzen zum Thema Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen in Kanada

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.

Mustererkennung und Bildverarbeitung, Maschinelles Sehen,    Radiologie (allgem.)

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.

Kurse und Veranstaltungen für Physikstudenten,    Kurse und Veranstaltungen für Studenten der Mathematik

Strategy Institute

AI and Machine Learning have evolved from a "nice-to-have" to an imperative for all organizations across all industries within the last year. It is your turn to build an AI and Machine Learning strategy by learning about the latest technologies and implementations from high-profile companies. Over a course of two full days, learn from TD, Air Canada, Modiface, LG, and more about proven strategies and detailed action plans. Our events allow for valuable networking opportunities with business leaders from across North America. Registration is limited - save you spot and join us on Sept 15-16, 2020 in Toronto, ON.

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