Prudencio Tossou

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it; #34,622 of 35,345 by trust here, #23,077 by citations
• Computer Vision and Pattern Recognition — 18 citations into it; #21,084 of 21,575 by trust here, #16,787 by citations
• Representation & Self-Supervised Learning — 12 citations into it
• Graph Learning — 10 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Materials Chemistry — 7 citations into it; #10,926 of 11,513 by trust here, #10,083 by citations
• Statistical Learning Theory — 5 citations into it

Whom Prudencio Tossou trusts overall

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

1. Christopher K. I. Williams
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Andrew Gordon Wilson
6. Gregory R. Koch
7. Alex Krizhevsky
8. Yann LeCun
9. Ruslan Salakhutdinov
10. Josh Tenenbaum

Who trusts Prudencio Tossou overall

1. Jake Snell
2. Timothy M. Hospedales
3. Massimiliano Patacchiola
4. Richard S. Zemel
5. Antreas Antoniou

Papers from Prudencio Tossou's perspective

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

Their papers

• Adaptive Deep Kernel Learning (2019) — 31 citations
• Rethinking Graph Transformers with Spectral Attention (2021) — 808 citations