T. Adalı
Cognitive Neuroscience · 2001–2015
A researcher in the Science corpus: 12 papers; trusts 57 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 85 citations into it; #527 of 10,852 by trust here, #741 by citations
- Signal Processing — 57 citations into it; #537 of 7,572 by trust here, #394 by citations
- Radiology, Nuclear Medicine and Imaging — 39 citations into it
- Artificial Intelligence — 20 citations into it; #29,006 of 35,345 by trust here, #22,463 by citations
- Analytical Chemistry — 15 citations into it; #1,158 of 1,254 by trust here, #741 by citations
- Statistics and Probability — 13 citations into it
- Computational Mathematics — 11 citations into it
- Natural Language Processing — 9 citations into it
Whom T. Adalı trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Anthony J. Bell
- Aapo Hyvärinen
- Vince D. Calhoun
- Christian F. Beckmann
- Hirotugu Akaike
- Jorma Rissanen
- Jean-François Cardoso
- Stephen M. Smith
- Terrence J. Sejnowski
- Olaf Sporns
Who trusts T. Adalı overall
- Vince D. Calhoun
- Yuhui Du
- Elena A. Allen
- Erik B. Erhardt
- Christian F. Beckmann
- Madiha J. Jafri
- Godfrey D. Pearlson
- Zening Fu
- Barnaly Rashid
- Martijn P. van den Heuvel
Papers from T. Adalı's perspective
Ordered by how strongly the researchers T. Adalı trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Dropout: a simple way to prevent neural networks from overfitting
- GENERATIVE ADVERSARIAL NETS
Their papers
- Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects (2015) — 1,143 citations
- The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery (2014) — 1,364 citations
- Multi-subject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery (2012) — 555 citations
- A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data (2011) — 411 citations
- Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety (2011) — 394 citations
- Comparison of multi-subject ICA methods for analysis of fMRI data (2010) — 718 citations
- Joint Blind Source Separation by Multi-set Canonical Correlation Analysis (2009) — 342 citations
- A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data (2008) — 1,216 citations
- Estimating the number of independent components for functional magnetic resonance imaging data (2007) — 939 citations
- Spatial and temporal independent component analysis of functional MRI data containing a pair of task‐related waveforms (2001) — 734 citations
- fMRI Activation in a Visual-Perception Task: Network of Areas Detected Using the General Linear Model and Independent Components Analysis (2001) — 324 citations
- A method for making group inferences from functional MRI data using independent component analysis (2001) — 3,068 citations