Aleksander Holynski
Computer Vision and Pattern Recognition · 2022–2025
A researcher in the Science corpus: 6 papers; trusts 465 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 269 citations into it; #12,656 of 21,575 by trust here, #6,031 by citations
- Computer Graphics and Computer-Aided Design — 106 citations into it
- Generative Models — 96 citations into it; #1,889 of 1,956 by trust here, #776 by citations
- Computational Mechanics — 63 citations into it
- Artificial Intelligence — 52 citations into it; #34,163 of 35,345 by trust here, #9,870 by citations
- Multimodal Learning — 44 citations into it
- Aerospace Engineering — 36 citations into it
- 3D Vision & Pose — 24 citations into it
Whom Aleksander Holynski trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jonathan Ho
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
Who trusts Aleksander Holynski overall
- Mingqiao Ye
- Haotian Liu
- Tao Yang
- Omer Bar-Tal
- Jing Shi
- Shuai Yang
- Chenshuang Zhang
- Lin Song
- Shaoteng Liu
- Kai Zhang
Papers from Aleksander Holynski's perspective
Ordered by how strongly the researchers Aleksander Holynski 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- GENERATIVE ADVERSARIAL NETS
Their papers
- InstructPix2Pix: Learning to Follow Image Editing Instructions (2022) — 3,195 citations
- Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions (2023) — 590 citations
- ReconFusion: 3D Reconstruction with Diffusion Priors (2023) — 374 citations
- CAT3D: Create Anything in 3D with Multi-View Diffusion Models (2024) — 457 citations
- Continuous 3D Perception Model with Persistent State (2025) — 511 citations
- Diffusion Self-Guidance for Controllable Image Generation (2023) — 397 citations