Bamdad Hosseini

This special session is organized by the PIMS kantorovich Initiative (kantorovich.org) which is dedicated towards research in the mathematics of Monge-Kantorovich optimal transport and its numerous applications to multiple areas of mathematics...

Generative models such as Generative Adversarial Nets (GANs), Variational Autoencoders and Normalizing Flows have been very successful in the unsupervised learning task of generating samples from a high-dimensional probability distribution. However...

Statistical and probabilistic methods are promising approaches to solving inverse problems – the process of recovering unknown parameters from indirect measurements. Of these, the Bayesian methods provide a principled approach to incorporating our...

Inverse problems (the problem of inferring an unknown parameter from indirect and noisy measurements) are ubiquitous in science and engineering. The Bayesian approach to inverse problems provides a probabilistic framework in which prior knowledge...

Graphical semi-supervised learning is the problem of labelling the verticess of a graph given the labels of a a few vertices along with geometric information about the graph. Such problems have attracted a lot of attention in machine learning for...

Generative models such as Generative Adversarial Nets (GANs), Variational Autoencoders and Normalizing Flows have been very successful in the unsupervised learning task of generating samples from a high-dimensional probability distribution. However...