Alexey A. Gritsenko
Computer Vision and Pattern Recognition · 2020–2024
A researcher in the Science corpus: 12 papers; trusts 709 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 333 citations into it; #6,071 of 21,575 by trust here, #2,102 by citations
- Artificial Intelligence — 318 citations into it; #34,682 of 35,345 by trust here, #8,007 by citations
- Generative Models — 115 citations into it; #1,884 of 1,956 by trust here, #567 by citations
- Evaluation & Benchmarks — 94 citations into it
- Model Architectures — 59 citations into it
- Signal Processing — 51 citations into it; #7,464 of 7,572 by trust here, #3,784 by citations
- Multimodal Learning — 47 citations into it
- Natural Language Processing — 46 citations into it
Whom Alexey A. Gritsenko trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Ross B. Girshick
- Ilya Sutskever
- Christian Szegedy
- Karen Simonyan
Who trusts Alexey A. Gritsenko overall
- Yuma Koizumi
- Neil Zeghidour
- Adam Polyak
- Xu Tan
- Mostafa Dehghani
- Alexandre D'efossez
- Zhaoxi Mu
- Ahmed Omran
- Hubert Siuzdak
- Shifeng Zhang
Papers from Alexey A. Gritsenko's perspective
Ordered by how strongly the researchers Alexey A. Gritsenko 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
- Going deeper with convolutions
Their papers
- Video Diffusion Models (2022) — 2,743 citations
- Imagen Video: High Definition Video Generation with Diffusion Models (2022) — 2,108 citations
- Scaling Vision Transformers to 22 Billion Parameters (2023) — 911 citations
- Simple Open-Vocabulary Object Detection with Vision Transformers (2022) — 421 citations
- SCENIC: A JAX Library for Computer Vision Research and Beyond (2021) — 78 citations
- The Benchmark Lottery (2021) — 147 citations
- Simple Open-Vocabulary Object Detection (2022) — 437 citations
- Scaling Open-Vocabulary Object Detection (2023) — 426 citations
- A Spectral Energy Distance for Parallel Speech Synthesis (2020) — 84 citations
- PaliGemma: A versatile 3B VLM for transfer (2024) — 728 citations
- When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards (2024) — 153 citations
- IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression (2020) — 68 citations