Jianyi Wang
Computer Vision and Pattern Recognition · AAAI Conference on Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 5 papers; trusts 699 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 190 citations into it; #9,743 of 21,575 by trust here, #13,815 by citations
- Artificial Intelligence — 125 citations into it
- Reinforcement Learning — 86 citations into it
- Generative Models — 58 citations into it
- Media Technology — 56 citations into it
- Evaluation & Benchmarks — 31 citations into it
- Management Science and Operations Research — 19 citations into it
- Statistical and Nonlinear Physics — 18 citations into it
Whom Jianyi Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- A. Bovik
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Jonathan Ho
- Yann LeCun
- Ilya Sutskever
- Jimmy Ba
Who trusts Jianyi Wang overall
- Zongsheng Yue
- Fanghua Yu
- X. Lin
- Tao Yang
- Yufei Wang
- Weixia Zhang
- Jingwen He
- Chen Change Loy
- Jinjin Gu
- Peiran Ren
Papers from Jianyi Wang's perspective
Ordered by how strongly the researchers Jianyi Wang 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
- Long Short-Term Memory
- 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
- Exploring CLIP for Assessing the Look and Feel of Images (2022) — 1,372 citations
- Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence (2019) — 37 citations
- Exploiting Diffusion Prior for Real-World Image Super-Resolution (2023) — 655 citations
- ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting (2023) — 569 citations
- Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards (2019) — 19 citations