Elan Rosenfeld
Artificial Intelligence · 2019–2025
A researcher in the Science corpus: 4 papers; trusts 160 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 105 citations into it; #7,755 of 35,345 by trust here, #6,848 by citations
- Safety, Robustness & Interpretability — 60 citations into it; #553 of 2,251 by trust here, #678 by citations
- Computer Vision and Pattern Recognition — 40 citations into it
- Representation & Self-Supervised Learning — 22 citations into it
- Statistics and Probability — 10 citations into it
- Electrical and Electronic Engineering — 9 citations into it
- Causal Inference & Discovery — 7 citations into it
- Molecular Biology — 6 citations into it
Whom Elan Rosenfeld trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- J. Bagnell
- Diederik P. Kingma
- Jan Peters
- Yann LeCun
- Radford M. Neal
- Ilya Sutskever
Who trusts Elan Rosenfeld overall
- Binghui Peng
- Evgenia Rusak
- Maksym Andriushchenko
- Huan Zhang
- Matthias Hein
- Alexander Meinke
- Xiaosen Wang
- Zifan Wang
- Hadi Salman
- Klas Leino
Papers from Elan Rosenfeld's perspective
Ordered by how strongly the researchers Elan Rosenfeld 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
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Certified Adversarial Robustness via Randomized Smoothing (2019) — 2,573 citations
- The Risks of Invariant Risk Minimization (2020) — 369 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization (2021) — 40 citations