Sofia Ira Ktena
Cognitive Neuroscience · 2017–2021
A researcher in the Science corpus: 8 papers; trusts 45 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 99 citations into it
- Radiology, Nuclear Medicine and Imaging — 78 citations into it; #2,918 of 3,265 by trust here, #1,628 by citations
- Artificial Intelligence — 60 citations into it; #34,663 of 35,345 by trust here, #11,921 by citations
- Computer Vision and Pattern Recognition — 46 citations into it; #20,611 of 21,575 by trust here, #19,766 by citations
- Graph Learning — 34 citations into it
- Statistical and Nonlinear Physics — 21 citations into it
- Model Architectures — 11 citations into it
- Computational Mechanics — 10 citations into it
Whom Sofia Ira Ktena trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Olaf Sporns
- Diederik P. Kingma
- Sergey Zagoruyko
- Pierre Vandergheynst
- Geoffrey E. Hinton
- Stephen M. Smith
- Michaël Defferrard
- Yann LeCun
- Alex Krizhevsky
- David K. Hammond
Who trusts Sofia Ira Ktena overall
- Sarah Parisot
- Xiao-Meng Zhang
- Michael M. Bronstein
- Federico Monti
- Nathanael Perraudin
- Arvid Lundervold
- Li Liang
- Yunsheng Bai
- Felipe Petroski Such
- Michaël Defferrard
Papers from Sofia Ira Ktena's perspective
Ordered by how strongly the researchers Sofia Ira Ktena 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
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks (2017) — 216 citations
- Swarm Learning for decentralized and confidential clinical machine learning (2021) — 792 citations
- Algorithmic amplification of politics on Twitter (2021) — 344 citations
- Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease (2018) — 743 citations
- Metric learning with spectral graph convolutions on brain connectivity networks (2018) — 375 citations
- Spectral Graph Convolutions for Population-based Disease Prediction (2017) — 250 citations
- Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex (2017) — 350 citations
- DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images (2017) — 85 citations