Eugene Brevdo
Artificial Intelligence · 2008–2021
A researcher in the Science corpus: 9 papers; trusts 58 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 124 citations into it; #11,987 of 35,345 by trust here, #3,859 by citations
- Computer Vision and Pattern Recognition — 71 citations into it; #12,442 of 21,575 by trust here, #3,323 by citations
- Probabilistic & Bayesian Methods — 57 citations into it; #1,270 of 1,525 by trust here, #568 by citations
- Reinforcement Learning — 41 citations into it; #1,260 of 2,242 by trust here, #1,300 by citations
- Generative Models — 25 citations into it
- Statistics and Probability — 18 citations into it
- Signal Processing — 12 citations into it
- Electrical and Electronic Engineering — 10 citations into it
Whom Eugene Brevdo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Radford M. Neal
- Diederik P. Kingma
- Yoshua Bengio
- Alex Graves
- Alex Krizhevsky
- Ilya Sutskever
- Richard S. Sutton
- Sepp Hochreiter
- Danilo Jimenez Rezende
Who trusts Eugene Brevdo overall
- Felix Stahlberg
- Sergey Levine
- Xu Tan
- Jesse Vig
- Bill Byrne
- Danielle Saunders
- Bo Li
- Tara N. Sainath
- Michael Janner
- Dustin Tran
Papers from Eugene Brevdo's perspective
Ordered by how strongly the researchers Eugene Brevdo 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
Their papers
- Tensor2Tensor for Neural Machine Translation (2018) — 553 citations
- Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion (2018) — 370 citations
- Deep Probabilistic Programming (2017) — 203 citations
- Dynamic control flow in large-scale machine learning (2018) — 112 citations
- Image processing for artist identification (2008) — 308 citations
- TensorFlow Distributions (2017) — 401 citations
- Reverb: A Framework For Experience Replay (2021) — 46 citations
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (2016) — 11,798 citations
- The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications (2011) — 509 citations