Michal Lukác
Computer Vision and Pattern Recognition · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 67 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 24 citations into it; #12,446 of 21,575 by trust here, #18,266 by citations
- Computer Graphics and Computer-Aided Design — 15 citations into it; #877 of 1,584 by trust here, #1,205 by citations
- Artificial Intelligence — 9 citations into it
- Generative Models — 9 citations into it; #1,141 of 1,956 by trust here, #1,766 by citations
- Optimization & Training — 6 citations into it
Whom Michal Lukác trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Karen Simonyan
- Aaron Hertzmann
- Alex Krizhevsky
- Individualized Treat
- Yoshua Bengio
- Yann LeCun
- Jimmy Ba
Who trusts Michal Lukác overall
Papers from Michal Lukác's perspective
Ordered by how strongly the researchers Michal Lukác 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)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (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
- GENERATIVE ADVERSARIAL NETS
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Differentiable vector graphics rasterization for editing and learning (2020) — 340 citations
- Im2Vec: Synthesizing Vector Graphics without Vector Supervision (2021) — 164 citations