121 citations · 299 across the 26 of their papers we have counts for
27 papers
Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning
Marcel Hussing, Jorge A. Mendez, Anisha Singrodia +2
Offline reinforcement learning (RL) is a promising direction that allows RL agents to pre-train on large datasets, avoiding the recurrence of expensive data collection. To advance…
Replicable Reinforcement Learning
Eric Eaton, Marcel Hussing, Michael Kearns +1
The replicability crisis in the social, behavioral, and data sciences has led to the formulation of algorithm frameworks for replicability -- i.e., a requirement that an algorithm…
ZeroFlow: Scalable Scene Flow via Distillation
Kyle Vedder, Neehar Peri, Nathaniel Chodosh +6
Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds. State-of-the-art methods use strong priors and test-time optimizatio…
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
Land Use Prediction using Electro-Optical to SAR Few-Shot Transfer Learning
Marcel Hussing, Karen Li, Eric Eaton
Satellite image analysis has important implications for land use, urbanization, and ecosystem monitoring. Deep learning methods can facilitate the analysis of different satellite m…
CompoSuite: A Compositional Reinforcement Learning Benchmark
Jorge A. Mendez, Marcel Hussing, Meghna Gummadi +1
We present CompoSuite, an open-source simulated robotic manipulation benchmark for compositional multi-task reinforcement learning (RL). Each CompoSuite task requires a particular…