Philipp Holl

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 62 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Statistical and Nonlinear Physics — 29 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Computational Mechanics — 24 citations into it
• Numerical Methods & Scientific Computing — 11 citations into it
• Model Architectures — 10 citations into it
• Control and Systems Engineering — 9 citations into it
• Reinforcement Learning — 9 citations into it

Whom Philipp Holl trusts overall

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

1. Adrien Treuille
2. Kaiming He
3. Paul J. Werbos
4. Gene H. Golub
5. Thomas R. Bewley
6. Diederik P. Kingma
7. Geoffrey E. Hinton
8. Maizar Raissi
9. Olaf Ronneberger
10. Alex Krizhevsky

Papers from Philipp Holl's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Learning to Control PDEs with Differentiable Physics (2020) — 231 citations
• Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers (2020) — 363 citations