Guy Tevet

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 4 papers; trusts 227 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 96 citations into it
• Generative Models — 38 citations into it
• Artificial Intelligence — 37 citations into it
• Control and Systems Engineering — 35 citations into it
• Computational Mechanics — 14 citations into it
• Statistical and Nonlinear Physics — 9 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Guy Tevet trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Ilya Sutskever
6. Jonathan Ho
7. Yann LeCun
8. Kaiming He
9. Ashish Vaswani
10. Alex Graves

Who trusts Guy Tevet overall

1. Mingyuan Zhang
2. Biao Jiang
3. Chuan Guo
4. Xin Chen
5. Yonatan Shafir
6. Roberto Gozalo-Brizuela
7. Taoran Yi
8. Tianxing He
9. Jo-Han Tseng
10. Thomas Scialom

Papers from Guy Tevet's perspective

Ordered by how strongly the researchers Guy Tevet trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Human Motion Diffusion Model (2022) — 1,358 citations
• Evaluating Text GANs as Language Models (2018) — 33 citations
• Human Motion Diffusion as a Generative Prior (2023) — 406 citations
• MotionCLIP: Exposing Human Motion Generation to CLIP Space (2022) — 555 citations