Surya Bhupatiraju
Artificial Intelligence · 2017–2025
A researcher in the Science corpus: 8 papers; trusts 90 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 160 citations into it; #9,270 of 35,345 by trust here, #4,829 by citations
- Computer Vision and Pattern Recognition — 75 citations into it; #6,975 of 21,575 by trust here, #5,843 by citations
- Reinforcement Learning — 51 citations into it; #858 of 2,242 by trust here, #695 by citations
- Natural Language Processing — 47 citations into it; #2,170 of 5,688 by trust here, #2,011 by citations
- Evaluation & Benchmarks — 40 citations into it; #2,776 of 3,147 by trust here, #2,743 by citations
- Model Architectures — 34 citations into it
- Optimization & Training — 19 citations into it
- Generative Models — 15 citations into it
Whom Surya Bhupatiraju trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- John Schulman
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Yoshua Bengio
- Ronald J. Williams
- Andrew Barto
- Alex Graves
- Alex Krizhevsky
Who trusts Surya Bhupatiraju overall
- Xinyun Chen
- Swarat Chaudhuri
- Augustus Odena
- Ali Borji
- Maxwell Nye
- Sergey Pankov
- Kevin Ellis
- Wangchunshu Zhou
- Scott Fujimoto
- Yaqian Zhang
Papers from Surya Bhupatiraju's perspective
Ordered by how strongly the researchers Surya Bhupatiraju 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- RobustFill: Neural Program Learning under Noisy I/O (2017) — 420 citations
- Skill Rating for Generative Models (2018) — 35 citations
- The Mirage of Action-Dependent Baselines in Reinforcement Learning (2018) — 145 citations
- Gemma 2: Improving Open Language Models at a Practical Size (2024) — 2,206 citations
- Gemma: Open Models Based on Gemini Research and Technology (2024) — 1,150 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Gemma 3 Technical Report (2025) — 1,621 citations
- Towards Mixed Optimization for Reinforcement Learning with Program Synthesis (2018) — 8 citations