activity
20232026
most citedMaIL: Improving Imitation Learning with Mamba

3 citations · 7 across the 18 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

stat.ML2024

Sequential Controlled Langevin Diffusions

Junhua Chen, Lorenz Richter, Julius Berner +3

An effective approach for sampling from unnormalized densities is based on the idea of gradually transporting samples from an easy prior to the complicated target distribution. Two…

cs.LG2024★ 1 cited

Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling

Denis Blessing, Xiaogang Jia, Johannes Esslinger +2

Monte Carlo methods, Variational Inference, and their combinations play a pivotal role in sampling from intractable probability distributions. However, current studies lack a unifi…

cs.LG2024★ 1 cited

Variational Distillation of Diffusion Policies into Mixture of Experts

Hongyi Zhou, Denis Blessing, Ge Li +4

This work introduces Variational Diffusion Distillation (VDD), a novel method that distills denoising diffusion policies into Mixtures of Experts (MoE) through variational inferenc…

cs.LG2024★ 3 cited

MaIL: Improving Imitation Learning with Mamba

Xiaogang Jia, Qian Wang, Atalay Donat +7

This work presents Mamba Imitation Learning (MaIL), a novel imitation learning (IL) architecture that provides an alternative to state-of-the-art (SoTA) Transformer-based policies.…

cs.RO2024★ 1 cited

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations

Xiaogang Jia, Denis Blessing, Xinkai Jiang +4

Imitation learning with human data has demonstrated remarkable success in teaching robots in a wide range of skills. However, the inherent diversity in human behavior leads to the…