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EE-735: Online learning in games

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PHYS-759: Nonequilibrum Physics for Complex Systems

We will discuss recent topics in nonequilibrium physics of complex living and artificial systems, ranging from collective behaviors in active matter to noise and information processing in cellular bio

EE-618: Theory and Methods for Reinforcement Learning

This course describes theory and methods for decision making under uncertainty under partial feedback.

BIO-642: State of the Art Topics in Neuroscience XIII

The Loss Landscape of Neural Networks is in general non-convex and rough, but recent mathematical results lead provide insights of practical relevance. 9 online lectures, lecturers from NYU, Stanford

AR-629: Transition workshop 2022 / Theory masterclass

Theoretical training on ecological transition with 21 internationally renowned experts. A concise introduction to the issues and dimensions of ecological transition by design; a cross-disciplinary ove

PHYS-203: Computational physics I

Aborder, formuler et résoudre des problèmes de physique en utilisant des méthodes numériques simples. Comprendre les avantages et les limites de ces méthodes (stabilité, convergence). Illustrer différ

MGT-529: Data science and machine learning II

This class discusses advanced data science and machine learning (ML) topics: Recommender Systems, Graph Analytics, and Deep Learning, Big Data, Data Clouds, APIs, Clustering. The course uses the Wol

BIOENG-450: In silico neuroscience

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.

CS-422: Database systems

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students

MICRO-513: Signal processing for functional brain imaging

Computational methods for the analysis of human brain imaging data

MSE-806: Spin-based devices for neuromorphic computing

The course entails a 5-days-program with lectures and exercises about spin-based computing and novel spin texture-based computing devices. An additional round table discussion and journal club session