Optimal transport (OT) has emerged as a powerful framework to compare
pr...
The Sliced-Wasserstein distance (SW) is a computationally efficient and
...
The Sliced-Wasserstein distance (SW) is being increasingly used in machi...
The idea of slicing divergences has been proven to be successful when
co...
Probability metrics have become an indispensable part of modern statisti...
Approximate Bayesian Computation (ABC) is a popular method for approxima...
Batch Reinforcement Learning (Batch RL) consists in training a policy us...
Minimum expected distance estimation (MEDE) algorithms have been widely ...
The Wasserstein distance and its variations, e.g., the sliced-Wasserstei...