Ankit Srivastava

Artificial Intelligence · with Finol · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Statistical and Nonlinear Physics — 21 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Computational Mechanics — 15 citations into it
• Mechanics of Materials — 13 citations into it
• Model Architectures — 13 citations into it
• Civil and Structural Engineering — 7 citations into it
• Computer Graphics and Computer-Aided Design — 7 citations into it

Whom Ankit Srivastava trusts overall

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

1. Michael S. Floater
2. Natarajan Sukumar
3. Hongkai Zhao
4. Gregory E. Fasshauer
5. Isaac E. Lagaris
6. Marino Arroyo
7. Yann LeCun
8. E. Weinan
9. Maizar Raissi
10. Jens Berg

Papers from Ankit Srivastava's perspective

Ordered by how strongly the researchers Ankit Srivastava 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. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. ImageNet: A large-scale hierarchical image database

Their papers

• Deep convolutional neural networks for eigenvalue problems in mechanics (2018) — 73 citations
• Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks (2021) — 446 citations