Denny Wu

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it
• Scaling & Learning Theory — 30 citations into it
• Statistical Learning Theory — 18 citations into it
• Statistics and Probability — 15 citations into it
• Optimization & Training — 11 citations into it

Whom Denny Wu trusts overall

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

1. Song Mei
2. Lénaïc Chizat
3. Andrea Montanari

Papers from Denny Wu's perspective

Ordered by how strongly the researchers Denny Wu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Understanding deep learning requires rethinking generalization
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Neural Tangent Kernel: Convergence and Generalization in Neural Networks
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
10. Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Their papers

• Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint (2020) — 78 citations