Ali Razavi
Artificial Intelligence · 2017–2022
A researcher in the Science corpus: 8 papers; trusts 614 researchers and is trusted by 1,673 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 235 citations into it; #6,240 of 35,345 by trust here, #1,991 by citations
- Computer Vision and Pattern Recognition — 211 citations into it; #1,001 of 21,575 by trust here, #1,019 by citations
- Generative Models — 96 citations into it; #225 of 1,956 by trust here, #342 by citations
- Representation & Self-Supervised Learning — 72 citations into it; #1,631 of 3,145 by trust here, #483 by citations
- Model Architectures — 44 citations into it; #2,276 of 2,278 by trust here, #1,794 by citations
- Optimization & Training — 38 citations into it
- Natural Language Processing — 33 citations into it
- Evaluation & Benchmarks — 31 citations into it; #1,574 of 3,147 by trust here, #574 by citations
Whom Ali Razavi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Aäron van den Oord
- Geoffrey E. Hinton
- Yoshua Bengio
- Danilo Jimenez Rezende
- Alex Krizhevsky
- Alex Graves
- Oriol Vinyals
- Ilya Sutskever
- Kaiming He
Who trusts Ali Razavi overall
- Jonathan Ho
- Jaemin Cho
- Arash Vahdat
- Sander Dieleman
- Prafulla Dhariwal
- Spyros Gidaris
- Alex Nichol
- Charlie Nash
- Mohit Bansal
- Yang Song
Papers from Ali Razavi's perspective
Ordered by how strongly the researchers Ali Razavi 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)
- 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
- 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
- Data-Efficient Image Recognition with Contrastive Predictive Coding (2019) — 1,574 citations
- Generating Diverse High-Fidelity Images with VQ-VAE-2 (2019) — 2,413 citations
- Population Based Training of Neural Networks (2017) — 896 citations
- A Generalist Agent (2022) — 1,117 citations
- Hyperbolic Attention Networks (2018) — 276 citations
- Preventing Posterior Collapse with delta-VAEs (2019) — 191 citations
- Predicting Video with VQVAE (2021) — 81 citations
- Do Transformers Need Deep Long-Range Memory? (2020) — 45 citations