Atri Rudra
Artificial Intelligence · 2001–2022
A researcher in the Science corpus: 13 papers; trusts 400 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 276 citations into it; #13,475 of 35,345 by trust here, #7,172 by citations
- Computer Vision and Pattern Recognition — 176 citations into it; #13,361 of 21,575 by trust here, #12,992 by citations
- Model Architectures — 160 citations into it; #840 of 2,278 by trust here, #379 by citations
- Efficiency & Compression — 98 citations into it; #616 of 1,264 by trust here, #252 by citations
- Signal Processing — 46 citations into it; #4,666 of 7,572 by trust here, #1,783 by citations
- Optimization & Training — 41 citations into it; #2,152 of 2,601 by trust here, #2,162 by citations
- Large Language Models — 39 citations into it
- Natural Language Processing — 35 citations into it
Whom Atri Rudra trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Ilya Sutskever
- Yann LeCun
- Jimmy Ba
- Alex Graves
- Quoc V. Le
Who trusts Atri Rudra overall
- Tri Dao
- David Canright
- Albert Gu
- Pawel Chodowiec
- Akashi Satoh
- Beidi Chen
- Daniel Y. Fu
- Sumio Morioka
- Kris Gaj
- Michael Poli
Papers from Atri Rudra's perspective
Ordered by how strongly the researchers Atri Rudra trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- HiPPO: Recurrent Memory with Optimal Polynomial Projections (2020) — 1,021 citations
- Hungry Hungry Hippos: Towards Language Modeling with State Space Models (2022) — 677 citations
- Scatterbrain: Unifying Sparse and Low-rank Attention Approximation (2021) — 175 citations
- Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers (2021) — 1,197 citations
- Monarch: Expressive Structured Matrices for Efficient and Accurate Training (2022) — 133 citations
- Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models (2021) — 95 citations
- FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness (2022) — 4,798 citations
- Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps (2020) — 56 citations
- Sparse Recovery for Orthogonal Polynomial Transforms (2019) — 5 citations
- Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations (2019) — 131 citations
- A Two-pronged Progress in Structured Dense Matrix Vector Multiplication (2018) — 31 citations
- Ordering by weighted number of wins gives a good ranking for weighted tournaments (2006) — 206 citations
- Efficient Rijndael Encryption Implementation with Composite Field Arithmetic (2001) — 312 citations