3 citations · 3 across the 1 of their papers we have counts for
4 papers
Differentiable Divergences Between Time Series
Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert
Computing the discrepancy between time series of variable sizes is notoriously challenging. While dynamic time warping (DTW) is popularly used for this purpose, it is not different…
Online Sinkhorn: Optimal Transport distances from sample streams
Arthur Mensch, Gabriel Peyré
Optimal Transport (OT) distances are now routinely used as loss functions in ML tasks. Yet, computing OT distances between arbitrary (i.e. not necessarily discrete) probability dis…
Geometric Losses for Distributional Learning
Arthur Mensch, Mathieu Blondel, Gabriel Peyré
Building upon recent advances in entropy-regularized optimal transport, and upon Fenchel duality between measures and continuous functions , we propose a generalization of the logi…
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch, Mathieu Blondel
Dynamic programming (DP) solves a variety of structured combinatorial problems by iteratively breaking them down into smaller subproblems. In spite of their versatility, DP algorit…