Clément Vignac

Molecular Biology · 2022

A researcher in the Science corpus: 3 papers; trusts 45 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 46 citations into it
• Materials Chemistry — 44 citations into it; #8,510 of 11,513 by trust here, #7,878 by citations
• Computational Theory and Mathematics — 41 citations into it; #10,442 of 12,182 by trust here, #3,033 by citations
• Generative Models — 41 citations into it
• Artificial Intelligence — 36 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Statistical and Nonlinear Physics — 15 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it

Whom Clément Vignac trusts overall

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

1. Diederik P. Kingma
2. Jonathan Ho
3. Geoffrey E. Hinton
4. Yang Song
5. Yoshua Bengio
6. Alex Krizhevsky
7. Prafulla Dhariwal
8. Jascha Narain Sohl-Dickstein
9. Yann LeCun
10. Max Welling

Who trusts Clément Vignac overall

1. Jiaxin Shi
2. Hanqun Cao
3. Zhiqing Sun

Papers from Clément Vignac's perspective

Ordered by how strongly the researchers Clément Vignac 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Equivariant Diffusion for Molecule Generation in 3D (2022) — 962 citations
• DiGress: Discrete Denoising diffusion for graph generation (2022) — 670 citations
• Equivariant 3D-conditional diffusion model for molecular linker design (2022) — 284 citations