Daniel Yukimura

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it; #21,560 of 35,345 by trust here, #29,412 by citations
• Scaling & Learning Theory — 11 citations into it
• Statistical and Nonlinear Physics — 7 citations into it

Whom Daniel Yukimura trusts overall

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

1. Phan-Minh Nguyen
2. Martin H. Anthony

Who trusts Daniel Yukimura overall

1. Jiaoyang Huang
2. Mao Ye

Papers from Daniel Yukimura's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Understanding deep learning requires rethinking generalization
3. Neural Tangent Kernel: Convergence and Generalization in Neural Networks
4. Gradient Descent Provably Optimizes Over-parameterized Neural Networks
5. A mean field view of the landscape of two-layer neural networks
6. Random Features for Large-Scale Kernel Machines
7. Neural Network Learning: Theoretical Foundations
8. A Note on Lazy Training in Supervised Differentiable Programming
9. Neural Networks as Interacting Particle Systems: Asymptotic Convexity of the Loss Landscape and Universal Scaling of the Approximation Error
10. Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit

Their papers

• A mean-field limit for certain deep neural networks (2019) — 72 citations