Hantian Zhang
Nuclear and High Energy Physics · 2016–2019
A researcher in the Science corpus: 5 papers; trusts 11 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Nuclear and High Energy Physics — 38 citations into it
- Artificial Intelligence — 32 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it
- Efficiency & Compression — 26 citations into it; #1,119 of 1,264 by trust here, #804 by citations
- Optimization & Training — 14 citations into it; #2,434 of 2,601 by trust here, #1,385 by citations
- Computational Theory and Mathematics — 7 citations into it
Whom Hantian Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Song Han
- Daisuke Miyashita
- Sébastien Bubeck
- Darryl Dexu Lin
- Mohammad Rastegari
- Scott E. Reed
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Huizi Mao
Who trusts Hantian Zhang overall
- Hanlin Tang
- Sebastian U. Stich
- Kumar Kshitij Patel
- Eduard A. Gorbunov
- Jinhyun So
- Antonio Polino
- Ahmed Khaled
- Aymeric Dieuleveut
- Ce Zhang
- Dan Alistarh
Papers from Hantian Zhang's perspective
Ordered by how strongly the researchers Hantian Zhang 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)
- Long Short-Term Memory
- 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
- Going deeper with convolutions
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- ALEX: An Updatable Adaptive Learned Index (2019) — 398 citations
- OpenLoops 2 (2019) — 471 citations
- Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit (2017) — 210 citations
- ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning (2017) — 213 citations
- The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning (2016) — 20 citations