Nathan A. Carr

2019

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

Papers from Nathan A. Carr's perspective

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

  1. Automatic differentiation in PyTorch
  2. A Compositional Object-Based Approach to Learning Physical Dynamics
  3. Interaction Networks for Learning about Objects, Relations and Physics
  4. TensorFlow: A system for large-scale machine learning
  5. Neural 3D Mesh Renderer
  6. The Tapenade automatic differentiation tool: Principles, model, and specification (TOMS)
  7. Stable fluids
  8. OpenDR: An Approximate Differentiable Renderer
  9. Flexible Neural Representation for Physics Prediction
  10. Theano: A CPU and GPU Math Compiler in Python

Their papers