Jacob Williams

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jacob Williams trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Sylvain Calinon

Papers from Jacob Williams's perspective

Ordered by how strongly the researchers Jacob Williams trusts endorse each paper. Same corpus, a different order for every researcher.

  1. A survey of robot learning from demonstration
  2. Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors
  3. On Learning, Representing, and Generalizing a Task in a Humanoid Robot
  4. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
  5. Learning grounded finite-state representations from unstructured demonstrations
  6. Probabilistic Movement Primitives
  7. Movement segmentation using a primitive library
  8. Open-source benchmarking for learned reaching motion generation in robotics
  9. An Algorithmic Perspective on Imitation Learning
  10. Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions

Their papers