Vinay Uday Prabhu
Artificial Intelligence · 2020–2023
A researcher in the Science corpus: 5 papers; trusts 249 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 108 citations into it
- Computer Vision and Pattern Recognition — 72 citations into it; #6,642 of 21,575 by trust here, #5,422 by citations
- Natural Language Processing — 65 citations into it
- Evaluation & Benchmarks — 43 citations into it; #1,051 of 3,147 by trust here, #497 by citations
- Safety, Robustness & Interpretability — 28 citations into it
- Safety Research — 12 citations into it; #914 of 5,829 by trust here, #1,585 by citations
- AI Ethics, Fairness & Society — 11 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
Whom Vinay Uday Prabhu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Jia Deng
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Karen Simonyan
- Yann LeCun
- Richard Socher
Who trusts Vinay Uday Prabhu overall
- Patrick Schramowski
- Stella Biderman
- Florian Tramèr
- Abeba Birhane
- Kristian Kersting
- Manuel Brack
- Dan Boneh
- Walter J. Scheirer
- Emily L. Denton
- Thomas Liao
Papers from Vinay Uday Prabhu's perspective
Ordered by how strongly the researchers Vinay Uday Prabhu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Multimodal datasets: misogyny, pornography, and malignant stereotypes (2021) — 486 citations
- Large image datasets: A pyrrhic win for computer vision? (2020) — 434 citations
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation (2021) — 104 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations