Pratyush Maini

Artificial Intelligence · 2019–2024

A researcher in the Science corpus: 3 papers; trusts 159 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it; #14,111 of 35,345 by trust here, #23,077 by citations
• Safety, Robustness & Interpretability — 53 citations into it; #953 of 2,251 by trust here, #1,945 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #10,584 of 21,575 by trust here, #20,271 by citations
• Signal Processing — 13 citations into it
• Large Language Models — 11 citations into it
• Model Architectures — 6 citations into it
• Privacy & Security — 6 citations into it; #373 of 709 by trust here, #690 by citations
• Natural Language Processing — 5 citations into it

Whom Pratyush Maini trusts overall

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

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

Who trusts Pratyush Maini overall

1. Adam Dziedzic
2. Eric Wong
3. Naveed Akhtar
4. Nikita Dhawan
5. Muhammad Ahmad Kaleem
6. Ruiqi Zhang
7. Leslie Rice
8. Ajmal Saeed Mian
9. Nicolas Papernot
10. Jonas Guan

Papers from Pratyush Maini's perspective

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

Their papers

• Dataset Inference: Ownership Resolution in Machine Learning (2021) — 171 citations
• Adversarial Robustness Against the Union of Multiple Perturbation Models (2019) — 175 citations
• TOFU: A Task of Fictitious Unlearning for LLMs (2024) — 510 citations