Searching for Optimal Runtime Assurance via Reachability and Reinforcement Learning

no code implementations • 6 Oct 2023 • Kristina Miller, Christopher K. Zeitler, William Shen, Kerianne Hobbs, Sayan Mitra, John Schierman, Mahesh Viswanathan

Our approach can guarantee safety while increasing utilization of the experimental controller over existing approaches.

reinforcement-learning

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation

1 code implementation • 27 Jul 2023 • William Shen, Ge Yang, Alan Yu, Jansen Wong, Leslie Pack Kaelbling, Phillip Isola

Self-supervised and language-supervised image models contain rich knowledge of the world that is important for generalization.

Few-Shot Learning Language Modelling

Learning Domain-Independent Planning Heuristics with Hypergraph Networks

no code implementations • 29 Nov 2019 • William Shen, Felipe Trevizan, Sylvie Thiébaux

We present the first approach capable of learning domain-independent planning heuristics entirely from scratch.

Taskonomy: Disentangling Task Transfer Learning

1 code implementation • CVPR 2018 • Amir Zamir, Alexander Sax, William Shen, Leonidas Guibas, Jitendra Malik, Silvio Savarese

The product is a computational taxonomic map for task transfer learning.

Multi-Task Learning

Feedback Networks

1 code implementation • CVPR 2017 • Amir R. Zamir, Te-Lin Wu, Lin Sun, William Shen, Jitendra Malik, Silvio Savarese

Currently, the most successful learning models in computer vision are based on learning successive representations followed by a decision layer.