Jiahao Li
Computer Vision and Pattern Recognition · 2021–2023
A researcher in the Science corpus: 3 papers; trusts 153 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 79 citations into it; #16,714 of 21,575 by trust here, #11,498 by citations
- Generative Models — 31 citations into it
- Computational Mechanics — 21 citations into it; #9,576 of 10,001 by trust here, #3,763 by citations
- Computer Graphics and Computer-Aided Design — 21 citations into it; #1,523 of 1,584 by trust here, #711 by citations
- Signal Processing — 17 citations into it
- Artificial Intelligence — 14 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
Whom Jiahao Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Johannes Ballé
- David C. Minnen
- Frank Bossen
- François Chollet
- Diederik P. Kingma
- George Toderici
- Geoffrey E. Hinton
- Guo Lu
- Alex Krizhevsky
- Anurag Ranjan
Who trusts Jiahao Li overall
Papers from Jiahao Li's perspective
Ordered by how strongly the researchers Jiahao Li 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- 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
- Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation (2022) — 701 citations
- Neural Video Compression with Diverse Contexts (2023) — 311 citations
- Deep Contextual Video Compression (2021) — 468 citations