Chen Zeno
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 3 papers; trusts 210 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 89 citations into it; #14,705 of 35,345 by trust here, #13,353 by citations
- Computer Vision and Pattern Recognition — 57 citations into it; #9,521 of 21,575 by trust here, #9,187 by citations
- Probabilistic & Bayesian Methods — 43 citations into it; #1,408 of 1,525 by trust here, #1,113 by citations
- Optimization & Training — 34 citations into it
- Representation & Self-Supervised Learning — 33 citations into it
- Efficiency & Compression — 10 citations into it
- Meta & Continual Learning — 10 citations into it; #934 of 1,041 by trust here, #848 by citations
- Model Architectures — 9 citations into it
Whom Chen Zeno trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Radford M. Neal
- Alex Graves
- Diederik P. Kingma
- Alex Krizhevsky
- David John Cameron MacKay
- Max Welling
- Yoshua Bengio
- Yann LeCun
- Kaiming He
Who trusts Chen Zeno overall
- Gido M. van de Ven
- James Smith
- Oleksiy Ostapenko
- Lucas Caccia
- Shuang Li
- Massimo Caccia
- Christian Henning
- Jorge Armando Mendez Mendez
- Onur Tasar
- Pau Rodr'iguez L'opez
Papers from Chen Zeno's perspective
Ordered by how strongly the researchers Chen Zeno 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Task Agnostic Continual Learning Using Online Variational Bayes (2018) — 130 citations
- Task-Agnostic Continual Learning Using Online Variational Bayes With Fixed-Point Updates (2020) — 51 citations
- Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning (2018) — 18 citations