Srikantan S. Nagarajan
Cognitive Neuroscience · 2001–2011
A researcher in the Science corpus: 14 papers; trusts 92 researchers and is trusted by 45 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 70 citations into it; #4,528 of 10,852 by trust here, #927 by citations
- Computational Mechanics — 41 citations into it; #2,267 of 10,001 by trust here, #3,029 by citations
- Signal Processing — 25 citations into it; #4,112 of 7,572 by trust here, #2,525 by citations
- Probabilistic & Bayesian Methods — 21 citations into it; #673 of 1,525 by trust here, #1,075 by citations
- Computer Vision and Pattern Recognition — 20 citations into it; #6,993 of 21,575 by trust here, #15,162 by citations
- Radiology, Nuclear Medicine and Imaging — 17 citations into it
- Cellular and Molecular Neuroscience — 12 citations into it
- Artificial Intelligence — 11 citations into it; #32,955 of 35,345 by trust here, #26,682 by citations
Whom Srikantan S. Nagarajan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Bhaskar D. Rao
- David L. Donoho
- Joel A. Tropp
- David John Cameron MacKay
- Karl J. Friston
- David M. Blei
- Robert Tibshirani
- Jean-Jacques Fuchs
- Michael E. Tipping
Who trusts Srikantan S. Nagarajan overall
- Zhilin Zhang
- Yu Zhang
- Bhaskar D. Rao
- David Paul Wipf
- Pasi Jylänki
- Christos Louizos
- Yin Zheng
- Dit-Yan Yeung
- E.J. Candes
- Francis R. Bach
Papers from Srikantan S. Nagarajan's perspective
Ordered by how strongly the researchers Srikantan S. Nagarajan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Topic regression multi-modal Latent Dirichlet Allocation for image annotation (2010) — 206 citations
- Iterative Reweighted 1 and 2 Methods for Finding Sparse Solutions (2010) — 466 citations
- Sensory Processing in Autism: A Review of Neurophysiologic Findings (2011) — 946 citations
- Measuring functional connectivity using MEG: Methodology and comparison with fcMRI (2011) — 519 citations
- Speech Production as State Feedback Control (2011) — 441 citations
- Latent Variable Bayesian Models for Promoting Sparsity (2011) — 318 citations
- A unified Bayesian framework for MEG/EEG source imaging (2009) — 393 citations
- Localization of neurosurgically implanted electrodes via photograph-MRI-radiograph coregistration (2008)
- A New View of Automatic Relevance Determination (2007) — 405 citations
- High Gamma Power Is Phase-Locked to Theta Oscillations in Human Neocortex (2006) — 2,649 citations
- A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data (2006) — 70 citations
- Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction (2005) — 480 citations
- Reconstructing spatio-temporal activities of neural sources using an MEG vector beamformer technique (2001) — 395 citations
- Speech comprehension is correlated with temporal response patterns recorded from auditory cortex (2001) — 542 citations