Yuhao Zhou
Computer Vision and Pattern Recognition · with Chen · 2017–2022
A researcher in the Science corpus: 3 papers; trusts 109 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 79 citations into it; #20,088 of 21,575 by trust here, #4,690 by citations
- Generative Models — 73 citations into it
- Artificial Intelligence — 62 citations into it; #32,962 of 35,345 by trust here, #8,007 by citations
- Probabilistic & Bayesian Methods — 44 citations into it
- Statistical and Nonlinear Physics — 28 citations into it
- Statistics and Probability — 13 citations into it
- Computational Mechanics — 8 citations into it
- Numerical Analysis — 7 citations into it
Whom Yuhao Zhou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alex Krizhevsky
- Geoffrey E. Hinton
- Radford M. Neal
- Jonathan Ho
- Yoshua Bengio
- Prafulla Dhariwal
- Alex Nichol
- Marlis Hochbruck
- Ilya Sutskever
Who trusts Yuhao Zhou overall
- Wenliang Zhao
- Xingchao Liu
- Hu Ye
- Moritz Reuss
- Simian Luo
- Neta Shaul
- Lianghua Huang
- Zhengyi Wang
- Hanqun Cao
- Tianwei Yin
Papers from Yuhao Zhou's perspective
Ordered by how strongly the researchers Yuhao Zhou trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- GENERATIVE ADVERSARIAL NETS
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps (2022) — 2,469 citations
- DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models (2022) — 1,074 citations
- ZhuSuan: A Library for Bayesian Deep Learning (2017) — 43 citations