Baskar Ganapathysubramanian

Computer Vision and Pattern Recognition · 2007–2019

A researcher in the Science corpus: 6 papers; trusts 28 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Artificial Intelligence — 26 citations into it
• Statistics and Probability — 15 citations into it; #2,271 of 12,932 by trust here, #4,253 by citations
• Environmental Engineering — 10 citations into it; #516 of 5,479 by trust here, #2,141 by citations
• Civil and Structural Engineering — 6 citations into it
• Numerical Analysis — 6 citations into it
• Computational Mechanics — 5 citations into it
• Computational Theory and Mathematics — 5 citations into it; #1,610 of 12,182 by trust here, #3,796 by citations

Whom Baskar Ganapathysubramanian trusts overall

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

1. Thomas Gerstner
2. C. Larrabee Winter
3. Dongbin Xiu
4. Ivo Babuska
5. Michael Griebel
6. Daniel M. Tartakovsky
7. G. Em Karniadakis
8. Geoffrey E. Hinton
9. Fabio Nobile
10. Yoshua Bengio

Who trusts Baskar Ganapathysubramanian overall

1. Anthony Nouy
2. Géraud Blatman
3. Fabio Nobile
4. Sondipon Adhikari
5. Bruno Sudret
6. Xiang Ma
7. Liang Yan
8. Raúl Tempone
9. Habib N. Najm
10. Ivo Babuska

Papers from Baskar Ganapathysubramanian's perspective

Ordered by how strongly the researchers Baskar Ganapathysubramanian 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. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Sparse grid collocation schemes for stochastic natural convection problems (2007) — 422 citations
• Plant disease identification using explainable 3D deep learning on hyperspectral images (2019) — 336 citations
• Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives. (2018) — 510 citations
• An explainable deep machine vision framework for plant stress phenotyping (2018) — 472 citations
• Machine Learning for High-Throughput Stress Phenotyping in Plants. (2016) — 928 citations
• Stability in the almost everywhere sense: A linear transfer operator approach (2010) — 49 citations