Tegan Maharaj

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 11 papers; trusts 292 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 349 citations into it; #22,927 of 35,345 by trust here, #2,822 by citations
• Computer Vision and Pattern Recognition — 138 citations into it
• Safety, Robustness & Interpretability — 123 citations into it; #1,995 of 2,251 by trust here, #306 by citations
• Economics and Econometrics — 45 citations into it
• Reinforcement Learning — 43 citations into it
• Model Architectures — 42 citations into it
• Optimization & Training — 42 citations into it
• Natural Language Processing — 41 citations into it

Whom Tegan Maharaj trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Kaiming He
6. Ilya Sutskever
7. Karen Simonyan
8. Yann LeCun
9. Christian Szegedy
10. Ronald J. Williams

Who trusts Tegan Maharaj overall

1. Rowan Zellers
2. Jie Lei
3. Devshree Patel
4. Amir Mazaheri
5. Linjie Li
6. Stephen Merity
7. Antoine Yang
8. Kamil Rocki
9. Licheng Yu
10. Yunseok Jang

Papers from Tegan Maharaj's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Closer Look at Memorization in Deep Networks (2017) — 2,230 citations
• Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations (2016) — 331 citations
• A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering (2016) — 113 citations
• Managing extreme AI risks amid rapid progress (2023) — 431 citations
• Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (2020) — 480 citations
• Hidden Incentives for Auto-Induced Distributional Shift (2020) — 57 citations
• Filling gaps in trustworthy development of AI (2021) — 63 citations
• Harms from Increasingly Agentic Algorithmic Systems (2023) — 259 citations
• Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics (2022) — 36 citations
• COVI White Paper (2020) — 30 citations
• Tackling Climate Change with Machine Learning (2019) — 1,184 citations