Odelia Schwartz
Cognitive Neuroscience · 2001–2018
A researcher in the Science corpus: 6 papers; trusts 98 researchers and is trusted by 48 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 65 citations into it; #472 of 10,852 by trust here, #1,694 by citations
- Computer Vision and Pattern Recognition — 39 citations into it
- Neuroscience — 26 citations into it; #70 of 487 by trust here, #163 by citations
- Cellular and Molecular Neuroscience — 22 citations into it; #1,661 of 2,998 by trust here, #2,766 by citations
- Artificial Intelligence — 16 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Signal Processing — 7 citations into it; #580 of 7,572 by trust here, #1,147 by citations
- Model Architectures — 6 citations into it
Whom Odelia Schwartz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David J. Heeger
- Eero P. Simoncelli
- Tatyana O. Sharpee
- Matteo Carandini
- Geoffrey E. Hinton
- Nicole C. Rust
- Peter S. Dayan
- David J. Field
- Barbara Olshausen
- L. V. D. van der Maaten
Who trusts Odelia Schwartz overall
- Zhou Wang
- Minjoon Kouh
- Siwei Lyu
- Eero P. Simoncelli
- Davide Zoccolan
- A. Bovik
- Tomaso A. Poggio
- Johannes Ballé
- Vincent Bonin
- Rajiv Soundararajan
Papers from Odelia Schwartz's perspective
Ordered by how strongly the researchers Odelia Schwartz trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Correspondence of Deep Neural Networks and the Brain for Visual Textures (2018) — 20 citations
- Spatiotemporal elements of macaque v1 receptive fields. (2005) — 508 citations
- Space and time in visual context (2007) — 151 citations
- Visual adaptation: neural, psychological and computational aspects. (2007) — 384 citations
- Spike-triggered neural characterization. (2006) — 465 citations
- Natural signal statistics and sensory gain control (2001) — 918 citations