Tomas Jakab
Computer Vision and Pattern Recognition · 2018
A researcher in the Science corpus: 1 paper; trusts 305 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 41 citations into it; #19,825 of 21,575 by trust here, #14,478 by citations
- Generative Models — 16 citations into it
- Artificial Intelligence — 8 citations into it
- Signal Processing — 6 citations into it
- Model Architectures — 5 citations into it
Whom Tomas Jakab trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yann LeCun
- Andrew Zisserman
- Karen Simonyan
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Ilya Sutskever
- Sepp Hochreiter
Who trusts Tomas Jakab overall
- Aliaksandr Siarohin
- Anand Gopalakrishnan
- S. Gadre
- Pitchaporn Rewatbowornwong
- Shirzad Amir
- Stéphane Lathuilière
- Aysegul Dundar
- Tejas D. Kulkarni
- Carl Doersch
- Sjoerd van Steenkiste
Papers from Tomas Jakab's perspective
Ordered by how strongly the researchers Tomas Jakab trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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
- Unsupervised Learning of Object Landmarks through Conditional Image Generation (2018) — 271 citations