Philipp Moritz
Artificial Intelligence · 2015–2018
A researcher in the Science corpus: 8 papers; trusts 95 researchers and is trusted by 1,609 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 108 citations into it; #279 of 35,345 by trust here, #665 by citations
- Reinforcement Learning — 101 citations into it; #61 of 2,242 by trust here, #72 by citations
- Optimization & Training — 62 citations into it; #160 of 2,601 by trust here, #116 by citations
- Computer Networks and Communications — 35 citations into it; #2,392 of 9,886 by trust here, #4,405 by citations
- Computer Vision and Pattern Recognition — 32 citations into it; #14,381 of 21,575 by trust here, #11,286 by citations
- ML Systems & Hardware — 30 citations into it; #237 of 575 by trust here, #137 by citations
- Information Systems — 23 citations into it
- Management Science and Operations Research — 23 citations into it
Whom Philipp Moritz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Geoffrey E. Hinton
- Alex Krizhevsky
- Richard S. Sutton
- Yann LeCun
- Ilya Sutskever
- Yoshua Bengio
- Ronald J. Williams
- Diederik P. Kingma
- Sham M. Kakade
Who trusts Philipp Moritz overall
- Sergey Levine
- Pieter Abbeel
- Jakub Konecný
- Shixiang Shane Gu
- Yoshua Bengio
- Aravind Rajeswaran
- Ruslan Salakhutdinov
- Ofir Nachum
- Aryan Mokhtari
- Xue Bin Peng
Papers from Philipp Moritz's perspective
Ordered by how strongly the researchers Philipp Moritz trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Trust Region Policy Optimization (2015) — 8,139 citations
- High-Dimensional Continuous Control Using Generalized Advantage Estimation (2015) — 4,662 citations
- Ray: A Distributed Framework for Emerging AI Applications (2017) — 1,702 citations
- SparkNet: Training Deep Networks in Spark (2015) — 178 citations
- Tune: A Research Platform for Distributed Model Selection and Training (2018) — 1,129 citations
- Ray RLLib: A Composable and Scalable Reinforcement Learning Library (2017) — 181 citations
- A Linearly-Convergent Stochastic L-BFGS Algorithm (2015) — 262 citations
- RLlib: Abstractions for Distributed Reinforcement Learning (2017) — 1,043 citations