Vivek Ramanujan
Artificial Intelligence · with Farhadi · 2019–2023
A researcher in the Science corpus: 5 papers; trusts 321 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 185 citations into it; #31,663 of 35,345 by trust here, #10,065 by citations
- Computer Vision and Pattern Recognition — 173 citations into it; #19,478 of 21,575 by trust here, #7,092 by citations
- Efficiency & Compression — 52 citations into it; #892 of 1,264 by trust here, #553 by citations
- Representation & Self-Supervised Learning — 42 citations into it
- Evaluation & Benchmarks — 40 citations into it
- Optimization & Training — 40 citations into it
- Model Architectures — 28 citations into it; #1,713 of 2,278 by trust here, #1,145 by citations
- Management Science and Operations Research — 13 citations into it
Whom Vivek Ramanujan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Sergey Ioffe
- Karen Simonyan
- Christian Szegedy
- Jia Deng
Who trusts Vivek Ramanujan overall
- Gyuhak Kim
- Haeyong Kang
- Changnan Xiao
- Victor Sanh
- Yingcong Li
- Zixuan Ke
- Tatsuya Konishi
- François Lagunas
- Eran Malach
- Zhenyu Cui
Papers from Vivek Ramanujan's perspective
Ordered by how strongly the researchers Vivek Ramanujan 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)
- 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
- DataComp: In search of the next generation of multimodal datasets (2023) — 734 citations
- What’s Hidden in a Randomly Weighted Neural Network? (2019) — 414 citations
- Soft Threshold Weight Reparameterization for Learnable Sparsity (2020) — 274 citations
- Forward Compatible Training for Large-Scale Embedding Retrieval Systems (2021) — 25 citations
- Supermasks in Superposition (2020) — 352 citations