Marissa A. Weis

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 30 citations into it
• Artificial Intelligence — 27 citations into it
• Safety, Robustness & Interpretability — 20 citations into it
• Generative Models — 13 citations into it
• Biophysics — 8 citations into it
• Cognitive Neuroscience — 8 citations into it

Whom Marissa A. Weis trusts overall

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

1. Diederik P. Kingma
2. Aäron van den Oord
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Nikolaus Kriegeskorte
6. Alex Krizhevsky
7. Christian Szegedy
8. Ilya Sutskever
9. Yann LeCun
10. Kaiming He

Papers from Marissa A. Weis's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Flexibly Fair Representation Learning by Disentanglement (2019) — 383 citations
• Diverse feature visualizations reveal invariances in early layers of deep neural networks (2018) — 34 citations