Pan Zhou
Computer Vision and Pattern Recognition · 2015–2023
A researcher in the Science corpus: 20 papers; trusts 1,961 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 646 citations into it; #7,622 of 21,575 by trust here, #2,718 by citations
- Artificial Intelligence — 569 citations into it; #23,627 of 35,345 by trust here, #5,059 by citations
- Model Architectures — 220 citations into it
- Optimization & Training — 157 citations into it
- Efficiency & Compression — 113 citations into it; #778 of 1,264 by trust here, #899 by citations
- Representation & Self-Supervised Learning — 77 citations into it; #2,330 of 3,145 by trust here, #1,338 by citations
- Computational Mechanics — 53 citations into it
- Generative Models — 48 citations into it
Whom Pan Zhou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Yann LeCun
- Karen Simonyan
- Christian Szegedy
Who trusts Pan Zhou overall
- Junnan Li
- Yun Miao
- Weihao Yu
- Alireza Fallah
- Kaiyi Ji
- Mahmoud Assran
- Nikunj Saunshi
- Caiming Xiong
- Liqun Qi
- Mathilde Caron
Papers from Pan Zhou's perspective
Ordered by how strongly the researchers Pan Zhou 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)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Prototypical Contrastive Learning of Unsupervised Representations (2020) — 1,199 citations
- A Survey of Model Compression and Acceleration for Deep Neural Networks (2017) — 1,247 citations
- EnlightenGAN: Deep Light Enhancement Without Paired Supervision (2019) — 2,438 citations
- Masked Diffusion Transformer is a Strong Image Synthesizer (2023) — 312 citations
- Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges (2018) — 686 citations
- Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification (2017) — 333 citations
- Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning (2020) — 304 citations
- InceptionNeXt: When Inception Meets ConvNeXt (2023) — 350 citations
- Video Graph Transformer for Video Question Answering (2022) — 113 citations
- Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models (2022) — 313 citations
- Inception Transformer (2022) — 300 citations
- MetaFormer Baselines for Vision (2022) — 348 citations
- MetaFormer is Actually What You Need for Vision (2021) — 1,389 citations
- Federated Mutual Learning (2020) — 173 citations
- Efficient Meta Learning via Minibatch Proximal Update (2019) — 98 citations
- InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy (2018) — 93 citations
- Tensor Factorization for Low-Rank Tensor Completion (2018) — 345 citations
- Differentially Private Distributed Online Learning (2018) — 20 citations
- Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks (2018) — 511 citations
- Differentially Private Distributed Online Learning (2015) — 83 citations