Yoni Halpern
Artificial Intelligence · 2012–2021
A researcher in the Science corpus: 9 papers; trusts 56 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 95 citations into it; #20,735 of 35,345 by trust here, #6,569 by citations
- Computer Vision and Pattern Recognition — 53 citations into it
- Representation & Self-Supervised Learning — 22 citations into it
- Evaluation & Benchmarks — 14 citations into it
- Statistical Learning Theory — 9 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Reinforcement Learning — 6 citations into it
- Statistics and Probability — 5 citations into it; #9,287 of 12,932 by trust here, #9,233 by citations
Whom Yoni Halpern trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Anima Anandkumar
- Michael Shwe
- Charles Peter Elkan
- Geoffrey E. Hinton
- Usama M. Fayyad
- Kaiming He
- Diederik P. Kingma
- Alex Krizhevsky
- Christian Szegedy
- Jia Deng
Who trusts Yoni Halpern overall
- Yacine Jernite
- Fangzhou Liao
- Marzyeh Ghassemi
- Hrayr Harutyunyan
- Tian Bai
- Sebastian Gehrmann
- Jacob Steinhardt
- Harini Suresh
- Ming Liang
- Nicolas Gillis
Papers from Yoni Halpern's perspective
Ordered by how strongly the researchers Yoni Halpern trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World (2017) — 343 citations
- The Inclusive Images Competition (2019) — 19 citations
- A Practical Algorithm for Topic Modeling with Provable Guarantees (2012) — 462 citations
- Causally motivated shortcut removal using auxiliary labels (2021) — 84 citations
- Unsupervised Learning of Noisy-Or Bayesian Networks (2013) — 36 citations
- Learning a Health Knowledge Graph from Electronic Medical Records (2017) — 413 citations
- Fairness is not static: deeper understanding of long term fairness via simulation studies (2020) — 264 citations
- Electronic medical record phenotyping using the anchor and learn framework (2016) — 153 citations
- Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests (2013) — 24 citations