Xingchao Liu
Computer Vision and Pattern Recognition · 2021–2023
A researcher in the Science corpus: 3 papers; trusts 372 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 136 citations into it; #7,850 of 21,575 by trust here, #8,831 by citations
- Generative Models — 96 citations into it
- Artificial Intelligence — 87 citations into it; #22,445 of 35,345 by trust here, #14,181 by citations
- Statistical and Nonlinear Physics — 31 citations into it; #5,861 of 10,127 by trust here, #2,631 by citations
- Signal Processing — 19 citations into it
- Representation & Self-Supervised Learning — 15 citations into it
- Biophysics — 14 citations into it
- Optimization & Training — 13 citations into it
Whom Xingchao Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Tero Karras
- Yann LeCun
- Jonathan Ho
- Ilya Sutskever
- Yang Song
Who trusts Xingchao Liu overall
- Tianwei Yin
- Axel Sauer
- Michael S. Albergo
- Michael Gharbi
- Richard Zhang
- Dominik Lorenz
- Nanye Ma
- Nicholas Matthew Boffi
- Alexander Tong
- Yufei Wang
Papers from Xingchao Liu's perspective
Ordered by how strongly the researchers Xingchao Liu 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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
- Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow (2022) — 3,494 citations
- InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation (2023) — 407 citations
- Conflict-Averse Gradient Descent for Multi-task Learning (2021) — 602 citations