Abhay Kumar Yadav

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 204 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #34,962 of 35,345 by trust here, #23,731 by citations
• Computer Vision and Pattern Recognition — 60 citations into it
• Optimization & Training — 50 citations into it; #1,710 of 2,601 by trust here, #1,419 by citations
• Computational Mechanics — 28 citations into it
• Generative Models — 21 citations into it
• Model Architectures — 14 citations into it
• Statistics and Probability — 14 citations into it
• Statistical Learning Theory — 12 citations into it

Whom Abhay Kumar Yadav trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Yann LeCun
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Kaiming He
7. Matthew D. Zeiler
8. Jimmy Ba
9. L. Eon Bottou
10. Ilya Sutskever

Who trusts Abhay Kumar Yadav overall

1. Sharan Vaswani
2. Gauthier Gidel
3. Divya Saxena
4. Tengyuan Liang
5. Soham De
6. Yu-Guan Hsieh
7. Lukas Balles
8. Jiannong Cao
9. James Stokes
10. Aaron Mishkin

Papers from Abhay Kumar Yadav's perspective

Ordered by how strongly the researchers Abhay Kumar Yadav 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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

• On the Similarity between the Laplace and Neural Tangent Kernels (2020) — 116 citations
• Automated Inference with Adaptive Batches (2017) — 85 citations
• Stabilizing Adversarial Nets With Prediction Methods (2017) — 92 citations
• Big Batch SGD: Automated Inference using Adaptive Batch Sizes (2016) — 64 citations