James Thornton
Computer Vision and Pattern Recognition · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 73 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 40 citations into it
- Generative Models — 40 citations into it; #1,765 of 1,956 by trust here, #1,577 by citations
- Artificial Intelligence — 32 citations into it
- Statistical and Nonlinear Physics — 27 citations into it
- Probabilistic & Bayesian Methods — 12 citations into it; #1,420 of 1,525 by trust here, #1,075 by citations
- Signal Processing — 11 citations into it
- Applied Mathematics — 9 citations into it
- Statistics and Probability — 9 citations into it
Whom James Thornton trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yang Song
- Diederik P. Kingma
- Aapo Hyvärinen
- Geoffrey E. Hinton
- Pascal Vincent
- Jonathan Ho
- Marco Cuturi
- Yoshua Bengio
- Alex Krizhevsky
- Stefano Ermon
Who trusts James Thornton overall
Papers from James Thornton's perspective
Ordered by how strongly the researchers James Thornton 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling (2021) — 746 citations
- Riemannian Score-Based Generative Modeling (2022) — 278 citations