Subhaneil Lahiri
Nuclear and High Energy Physics · 2006–2016
A researcher in the Science corpus: 5 papers; trusts 42 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Nuclear and High Energy Physics — 50 citations into it; #3,455 of 6,161 by trust here, #3,520 by citations
- Artificial Intelligence — 24 citations into it; #10,816 of 35,345 by trust here, #7,797 by citations
- Astronomy and Astrophysics — 23 citations into it; #6,210 of 10,964 by trust here, #6,742 by citations
- Statistical and Nonlinear Physics — 19 citations into it; #1,960 of 10,127 by trust here, #687 by citations
- Computational Mechanics — 18 citations into it
- Cognitive Neuroscience — 16 citations into it; #2,391 of 10,852 by trust here, #1,946 by citations
- Geometry and Topology — 16 citations into it
- Electrical and Electronic Engineering — 12 citations into it
Whom Subhaneil Lahiri trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John J. Hopfield
- Haim Sompolinsky
- E. Gardner
- David L. Donoho
- Stefano Fusi
- Nicolas J.-B. Brunel
- Judea Pearl
- G. W. Gibbons
- E.J. Candes
- Barbara Olshausen
Who trusts Subhaneil Lahiri overall
- Greg Yang
- Boris Hanin
- Sam Schoenholz
- Marcus K. Benna
- Soufiane Hayou
- Jeffrey Pennington
- Surya Ganguli
- Stefano Fusi
- Friedemann Zenke
- Lechao Xiao
Papers from Subhaneil Lahiri's perspective
Ordered by how strongly the researchers Subhaneil Lahiri trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Human-level control through deep reinforcement learning
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Exponential expressivity in deep neural networks through transient chaos (2016) — 683 citations
- Statistical mechanics of complex neural systems and high dimensional data (2013) — 79 citations
- A memory frontier for complex synapses (2013) — 58 citations
- Large rotating AdS black holes from fluid mechanics (2007) — 183 citations
- Supersymmetric states of N=4 Yang-Mills from giant gravitons (2006) — 160 citations