Shagun Sodhani

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 13 papers; trusts 659 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 433 citations into it; #9,317 of 35,345 by trust here, #5,788 by citations
• Computer Vision and Pattern Recognition — 181 citations into it; #7,133 of 21,575 by trust here, #8,122 by citations
• Reinforcement Learning — 181 citations into it
• Representation & Self-Supervised Learning — 72 citations into it; #2,260 of 3,145 by trust here, #1,692 by citations
• Model Architectures — 60 citations into it; #1,045 of 2,278 by trust here, #950 by citations
• Natural Language Processing — 57 citations into it; #4,804 of 5,688 by trust here, #3,897 by citations
• Safety, Robustness & Interpretability — 53 citations into it
• Meta & Continual Learning — 44 citations into it; #451 of 1,041 by trust here, #543 by citations

Whom Shagun Sodhani trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Richard S. Sutton
5. Alex Krizhevsky
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Alex Graves
10. J. Urgen Schmidhuber

Who trusts Shagun Sodhani overall

1. Haoxuan Qu
2. Pranshu Malviya
3. Magdalena Biesialska
4. Shenyang Huang
5. Zirui Wang
6. Riccardo Del Chiaro
7. Bo Liu
8. Marc Masana
9. Tyler L. Hayes
10. Sanket Vaibhav Mehta

Papers from Shagun Sodhani's perspective

Ordered by how strongly the researchers Shagun Sodhani trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training (2022) — 495 citations
• Learning Powerful Policies by Using Consistent Dynamics Model (2019) — 5 citations
• Invariant Causal Prediction for Block MDPs (2020) — 159 citations
• Multi-Task Reinforcement Learning with Context-based Representations (2021) — 259 citations
• Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (2020) — 480 citations
• Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives (2019) — 55 citations
• CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (2019) — 274 citations
• Toward Training Recurrent Neural Networks for Lifelong Learning (2019) — 101 citations
• Environments for Lifelong Reinforcement Learning (2018) — 8 citations
• Block Contextual MDPs for Continual Learning (2021) — 34 citations
• IIRC: Incremental Implicitly-Refined Classification (2020) — 32 citations
• Recurrent Independent Mechanisms (2019) — 369 citations
• On Training Recurrent Neural Networks for Lifelong Learning (2018) — 19 citations