Satrajit S. Ghosh
Cognitive Neuroscience · 2006–2020
A researcher in the Science corpus: 14 papers; trusts 19 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 144 citations into it; #2,875 of 10,852 by trust here, #1,210 by citations
- Radiology, Nuclear Medicine and Imaging — 94 citations into it
- Artificial Intelligence — 51 citations into it
- Computer Vision and Pattern Recognition — 36 citations into it
- Experimental and Cognitive Psychology — 25 citations into it; #2,753 of 9,731 by trust here, #4,444 by citations
- Information Systems — 11 citations into it
- Safety, Robustness & Interpretability — 11 citations into it
- Information Systems and Management — 10 citations into it
Whom Satrajit S. Ghosh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Poeppel
- Diederik P. Kingma
- Bruce Fischl
- Robert J. Zatorre
- Arno Klein
- Geoffrey E. Hinton
- Daniel S. Marcus
- Scott M. Lundberg
- Bryce Goodman
- Naveed Akhtar
Who trusts Satrajit S. Ghosh overall
Papers from Satrajit S. Ghosh's perspective
Ordered by how strongly the researchers Satrajit S. Ghosh trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Distributed Weight Consolidation: A Brain Segmentation Case Study (2018) — 28 citations
- Neural modeling and imaging of the cortical interactions underlying syllable production. (2006) — 934 citations
- The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments (2016) — 1,663 citations
- Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study (2020) — 313 citations
- The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data (2020)
- Automated assessment of psychiatric disorders using speech: A systematic review (2019) — 489 citations
- Functional gradients of the cerebellum (2018) — 382 citations
- FMRIPrep: a robust preprocessing pipeline for functional MRI (2018) — 3,579 citations
- BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods (2016) — 311 citations
- Mindboggling morphometry of human brains (2016) — 680 citations
- NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain (2014) — 592 citations
- Data sharing in neuroimaging research (2012) — 296 citations
- Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python (2011) — 2,091 citations
- Evaluation of volume-based and surface-based brain image registration methods (2010)