Markov Chain Monte Carlo (MCMC) is a powerful algorithmic framework for sampling from complex probability distributions. Standard MCMC methods struggle with high-dimensional distributions containing well-separated modes, becoming trapped in local regions. Replica-exchange/Parallel tempering (PT) addresses this by using intermediate annealing distributions to bridge a tractable reference (e.g., Gaussian) and an intractable target distribution. However, classical […]

Over the past few years, it has become clear that cancer cells have remarkable adaptive properties that enable them to become resistant to therapies, evade the immune system, and successfully migrate from the primary tumor to metastatic sites. This talk will focus on how cells can pick up these adaptive properties by making use of […]

We give a strongly polynomial algorithm for minimum cost generalized flow, and as a consequence, for all linear programs with at most two nonzero entries per row or column. Previously, strongly polynomial algorithms were only known for the primal and dual feasibility problems. Our approach is to show that the path-following interior point method of […]