1 citations · 1 across the 3 of their papers we have counts for
3 papers
SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
Jongmin Lee, Meiqi Sun, Pieter Abbeel
In the unsupervised pre-training for reinforcement learning, the agent aims to learn a prior policy for downstream tasks without relying on task-specific reward functions. We focus…
eIQ Neutron: Redefining Edge-AI Inference with Integrated NPU and Compiler Innovations
Lennart Bamberg, Filippo Minnella, Roberto Bosio +5
Neural Processing Units (NPUs) are key to enabling efficient AI inference in resource-constrained edge environments. While peak tera operations per second (TOPS) is often used to g…
Body Transformer: Leveraging Robot Embodiment for Policy Learning
Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu +2
In recent years, the transformer architecture has become the de facto standard for machine learning algorithms applied to natural language processing and computer vision. Despite n…