Itay Golan
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 5 papers; trusts 300 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 132 citations into it; #13,474 of 35,345 by trust here, #8,439 by citations
- Computer Vision and Pattern Recognition — 84 citations into it; #8,832 of 21,575 by trust here, #7,027 by citations
- Optimization & Training — 72 citations into it; #2,436 of 2,601 by trust here, #1,661 by citations
- Probabilistic & Bayesian Methods — 43 citations into it; #1,409 of 1,525 by trust here, #1,113 by citations
- Representation & Self-Supervised Learning — 36 citations into it
- Model Architectures — 20 citations into it
- Efficiency & Compression — 15 citations into it
- Statistical and Nonlinear Physics — 15 citations into it; #8,804 of 10,127 by trust here, #2,503 by citations
Whom Itay Golan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Radford M. Neal
- Alex Krizhevsky
- Alex Graves
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- David John Cameron MacKay
- Max Welling
Who trusts Itay Golan overall
- Gido M. van de Ven
- James Smith
- Oleksiy Ostapenko
- Lucas Caccia
- Shuang Li
- Massimo Caccia
- Christian Henning
- Jorge Armando Mendez Mendez
- Onur Tasar
- Gunshi Gupta
Papers from Itay Golan's perspective
Ordered by how strongly the researchers Itay Golan 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Task Agnostic Continual Learning Using Online Variational Bayes (2018) — 130 citations
- Norm matters: efficient and accurate normalization schemes in deep networks (2018) — 191 citations
- Kernel and Rich Regimes in Overparametrized Models (2019) — 437 citations
- Task-Agnostic Continual Learning Using Online Variational Bayes With Fixed-Point Updates (2020) — 51 citations
- Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning (2018) — 18 citations