Ayush Jaiswal

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 6 papers; trusts 439 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 98 citations into it; #21,099 of 21,575 by trust here, #10,010 by citations
• Artificial Intelligence — 57 citations into it
• Generative Models — 40 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it
• Signal Processing — 9 citations into it

Whom Ayush Jaiswal trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Yann LeCun
5. Yoshua Bengio
6. Ilya Sutskever
7. Kaiming He
8. Jeff Donahue
9. Ruslan Salakhutdinov
10. Sepp Hochreiter

Who trusts Ayush Jaiswal overall

1. Adam R. Kosiorek
2. Yuzi He
3. Ninareh Mehrabi
4. Wael AbdAlmageed
5. Divya Saxena
6. Chaochao Lu
7. Premkumar Natarajan
8. Sara Sabour
9. Keith A. Burghardt
10. Greg Ver Steeg

Papers from Ayush Jaiswal's perspective

Ordered by how strongly the researchers Ayush Jaiswal 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Recurrent Convolutional Strategies for Face Manipulation Detection in Videos (2019) — 581 citations
• CapsuleGAN: Generative Adversarial Capsule Network (2018) — 169 citations
• Bidirectional Conditional Generative Adversarial Networks (2017) — 42 citations
• Unsupervised Adversarial Invariance (2018) — 52 citations
• Invariant Representations through Adversarial Forgetting (2019) — 47 citations
• Large-Scale Unsupervised Deep Representation Learning for Brain Structure (2018) — 5 citations