Boris Bonev

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 3 papers; trusts 236 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it; #16,615 of 21,575 by trust here, #20,271 by citations
• Artificial Intelligence — 26 citations into it
• Computational Mechanics — 19 citations into it; #7,657 of 10,001 by trust here, #8,947 by citations
• Computer Graphics and Computer-Aided Design — 14 citations into it; #1,203 of 1,584 by trust here, #1,447 by citations
• Atmospheric Science — 9 citations into it
• Generative Models — 9 citations into it
• Global and Planetary Change — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Boris Bonev trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yann LeCun
5. Yoshua Bengio
6. Ross B. Girshick
7. Diederik P. Kingma
8. Kaiming He
9. Alexey Dosovitskiy
10. Ilya Sutskever

Who trusts Boris Bonev overall

1. Steffen Wiewel
2. Pingchuan Ma
3. Moritz Becher
4. Nils Thürey
5. Yunsheng Tian
6. Stephan Rasp

Papers from Boris Bonev's perspective

Ordered by how strongly the researchers Boris Bonev trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere (2023) — 322 citations
• Pre-computed Liquid Spaces with Generative Neural Networks and Optical Flow (2017) — 15 citations
• Generating Liquid Simulations with Deformation-aware Neural Networks (2017) — 16 citations