Probability Distribution

Probability distributions are fundamental mathematical objects describing the likelihood of different outcomes in a random process, with research focusing on understanding and manipulating these distributions for various applications. Current research emphasizes developing methods for learning and modeling complex, high-dimensional distributions, including those arising in deep learning, using techniques like normalizing flows, variational autoencoders, and novel clustering algorithms based on optimal transport or extreme value theory. These advancements have significant implications across diverse fields, from improving the robustness and safety of large language models to optimizing drug selection in cancer therapy and enhancing the efficiency of Bayesian optimization.