Shreyas Padhy

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 68 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 102 citations into it; #31,649 of 35,345 by trust here, #19,439 by citations
• Computer Vision and Pattern Recognition — 55 citations into it; #20,206 of 21,575 by trust here, #15,529 by citations
• Safety, Robustness & Interpretability — 34 citations into it
• Probabilistic & Bayesian Methods — 30 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Optimization & Training — 16 citations into it
• Statistical Learning Theory — 8 citations into it
• Statistics and Probability — 8 citations into it

Whom Shreyas Padhy trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Dan Hendrycks
4. Diederik P. Kingma
5. Yoshua Bengio
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Christian Szegedy
10. Sergey Ioffe

Who trusts Shreyas Padhy overall

1. Marvin Zhang
2. Stanislav Fort
3. Shuaicheng Niu

Papers from Shreyas Padhy's perspective

Ordered by how strongly the researchers Shreyas Padhy 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift (2020) — 332 citations
• A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection (2021) — 310 citations
• Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness (2020) — 573 citations