Bram Wallace

Computer Vision and Pattern Recognition · 2019–2023

A researcher in the Science corpus: 3 papers; trusts 325 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #12,467 of 21,575 by trust here, #14,822 by citations
• Artificial Intelligence — 40 citations into it; #24,855 of 35,345 by trust here, #27,551 by citations
• Generative Models — 33 citations into it
• Computer Graphics and Computer-Aided Design — 15 citations into it
• Statistical and Nonlinear Physics — 13 citations into it; #7,735 of 10,127 by trust here, #7,747 by citations
• 3D Vision & Pose — 12 citations into it; #525 of 689 by trust here, #679 by citations
• Computational Mechanics — 11 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Bram Wallace trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Matthew D. Zeiler
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Ross B. Girshick
10. Laurent Dinh

Who trusts Bram Wallace overall

1. Meng Tian
2. Inbar Huberman-Spiegelglas
3. Chenshuang Zhang
4. Marcelo H. Ang Jr.
5. Vladimir Kulikov
6. Tianwei Yin
7. Chaoning Zhang
8. Gim Hee Lee

Papers from Bram Wallace's perspective

Ordered by how strongly the researchers Bram Wallace 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Diffusion Model Alignment Using Direct Preference Optimization (2023) — 819 citations
• Few-Shot Generalization for Single-Image 3D Reconstruction via Priors (2019) — 45 citations
• EDICT: Exact Diffusion Inversion via Coupled Transformations (2022) — 308 citations