activity
20182024
most citedTACO: Learning Task Decomposition via Temporal Alignment for Control

36 citations · 47 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 3 cited

emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation

Sasha Salter, Richard Warren, Collin Schlager +11

Hands are the primary means through which humans interact with the world. Reliable and always-available hand pose inference could yield new and intuitive control schemes for human-…

cs.LG2022★ 1 cited

MO2: Model-Based Offline Options

Sasha Salter, Markus Wulfmeier, Dhruva Tirumala +4

The ability to discover useful behaviours from past experience and transfer them to new tasks is considered a core component of natural embodied intelligence. Inspired by neuroscie…

cs.AI2022★ 1 cited

Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning

Sasha Salter, Kristian Hartikainen, Walter Goodwin +1

The ability to discover behaviours from past experience and transfer them to new tasks is a hallmark of intelligent agents acting sample-efficiently in the real world. Equipping em…

cs.AI2019★ 6 cited

Attention-Privileged Reinforcement Learning

Sasha Salter, Dushyant Rao, Markus Wulfmeier +2

Image-based Reinforcement Learning is known to suffer from poor sample efficiency and generalisation to unseen visuals such as distractors (task-independent aspects of the observat…

cs.LG2018★ 36 cited

TACO: Learning Task Decomposition via Temporal Alignment for Control

Kyriacos Shiarlis, Markus Wulfmeier, Sasha Salter +2

Many advanced Learning from Demonstration (LfD) methods consider the decomposition of complex, real-world tasks into simpler sub-tasks. By reusing the corresponding sub-policies wi…