Sort by
Refine Your Search
-
an excellent publication record. Solid research experience in one or more of the following topics is expected: Graph neural networks Optimization algorithms Predicting structured output Self-supervised learning
-
chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will
-
chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will
-
particle systems, and mixing times of Markov chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in
-
chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will
-
expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on RL and graph neural networks (GNNs) demonstrate some of our key research