1 citations · 3 across the 3 of their papers we have counts for
4 papers
Scalable Pre-training of Large Autoregressive Image Models
Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai +5
This paper introduces AIM, a collection of vision models pre-trained with an autoregressive objective. These models are inspired by their textual counterparts, i.e., Large Language…
Predicting Ordinary Differential Equations with Transformers
Sören Becker, Michal Klein, Alexander Neitz +2
We develop a transformer-based sequence-to-sequence model that recovers scalar ordinary differential equations (ODEs) in symbolic form from irregularly sampled and noisy observatio…
Unbalanced Low-rank Optimal Transport Solvers
Meyer Scetbon, Michal Klein, Giovanni Palla +1
The relevance of optimal transport methods to machine learning has long been hindered by two salient limitations. First, the computational cost of standard sample-based so…
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps
Marco Cuturi, Michal Klein, Pierre Ablin
Optimal transport (OT) theory focuses, among all maps that can morph a probability measure onto another, on those that are the ``thriftiest…