Our work 'Action Conditional Recurrent Kalman Network' is accepted at #CoRL2020. Excited to share more details at the virtual conf. :) Thanks to Prof Gerhard Neuman(@alr_kit) and our collaborators Philipp Becker, Dieter Büchler, Marc Hanheide, L-CAS. arxiv.org/abs/2010.10201

Our work ‚Specializing Versatile Skill Libraries using Local Mixture of Experts‘ is accepted at #CoRL2021 🙂. openreview.net/forum?id=j3Rgu… Thanks to Prof. Neumann(@alr_kit), Zhou, Ge Li and Philipp Becker (Philipp Becker).

I am happy to share our recent work, “On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning”, ( openreview.net/pdf?id=UQXdQyo… ) published at TMLR. With Gerhard Neumann Let me summarize our key contributions in a short thread:

Can we teach dexterous robot hands manipulation without human demos or hand-crafted rewards? Our key insight: Use Vision-Language Models (VLMs) to scaffold coarse motion plans, then train an RL agent to execute them with 3D keypoints as the interface. 1/7

I couldn’t make it to #ICML2025, but our work on Diffusion-Based Maximum Entropy RL is there! We introduce DiME, a new approach that swaps the standard actor in MaxEnt RL with a conditional diffusion model. This bypasses the need for tricky entropy approximations and lets our