Imitation learning (IL) seeks to teach agents specific tasks through exp...
With the advent of large datasets, offline reinforcement learning (RL) i...
Continuous Normalizing Flows (CNFs) are a class of generative models tha...
We study the use of amortized optimization to predict optimal transport ...
Cross-domain imitation learning studies how to leverage expert demonstra...
Modeling distributions on Riemannian manifolds is a crucial component in...
We study multi-marginal optimal transport, a generalization of optimal
t...
Gaussian processes (GPs) are nonparametric Bayesian models that have bee...
The Asymptotic Randomised Control (ARC) algorithm provides a rigorous
ap...
Barycentric averaging is a principled way of summarizing populations of
...
Dynamic time warping (DTW) is a useful method for aligning, comparing an...
In the FAME! Project, a code-switching (CS) automatic speech recognition...