Divyat Mahajan

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 152 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 51 citations into it; #21,466 of 35,345 by trust here, #22,463 by citations
• Computer Vision and Pattern Recognition — 30 citations into it
• Representation & Self-Supervised Learning — 26 citations into it
• Safety, Robustness & Interpretability — 15 citations into it
• Causal Inference & Discovery — 5 citations into it

Whom Divyat Mahajan trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Diederik P. Kingma
7. Ian J. Goodfellow
8. Ilya Sutskever
9. Christian Szegedy
10. Ross B. Girshick

Who trusts Divyat Mahajan overall

1. Nadia Burkart
2. Sahil Verma
3. Amir-Hossein Karimi
4. Jindong Wang
5. Marco F. Huber
6. John P. Dickerson
7. Cuiling Lan
8. Bernhard Schölkopf
9. Julius von Kügelgen
10. Keegan E. Hines

Papers from Divyat Mahajan's perspective

Ordered by how strongly the researchers Divyat Mahajan 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Domain Generalization using Causal Matching (2020) — 409 citations
• Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers (2019) — 240 citations