Lazar Valkov

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 3 papers; trusts 109 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it; #16,112 of 35,345 by trust here, #8,893 by citations
• Computer Vision and Pattern Recognition — 36 citations into it; #10,717 of 21,575 by trust here, #7,340 by citations
• Generative Models — 12 citations into it; #993 of 1,956 by trust here, #832 by citations
• Meta & Continual Learning — 8 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Neural Architecture Search & AutoML — 5 citations into it

Whom Lazar Valkov trusts overall

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

1. Yann LeCun
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ilya Sutskever
8. L. Eon Bottou
9. Ross B. Girshick
10. Quoc V. Le

Who trusts Lazar Valkov overall

1. Fei Ye
2. Swarat Chaudhuri
3. Ali Borji
4. Sayeri Lala
5. Senthil Purushwalkam
6. Jorge Armando Mendez Mendez
7. Adrian G. Bors
8. Adji Bousso Dieng
9. Kevin Ellis
10. Dan Friedman

Papers from Lazar Valkov's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning (2017) — 740 citations
• HOUDINI: Lifelong Learning as Program Synthesis (2018) — 86 citations
• A Probabilistic Framework for Modular Continual Learning (2023) — 5 citations