Jörn Diedrichsen
Cognitive Neuroscience · 2004–2022
A researcher in the Science corpus: 14 papers; trusts 82 researchers and is trusted by 53 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 182 citations into it; #1,469 of 10,852 by trust here, #1,650 by citations
- Social Psychology — 47 citations into it; #4,989 of 15,694 by trust here, #3,828 by citations
- Computer Vision and Pattern Recognition — 32 citations into it
- Radiology, Nuclear Medicine and Imaging — 25 citations into it; #163 of 3,265 by trust here, #1,136 by citations
- Neurology — 22 citations into it; #44 of 1,455 by trust here, #440 by citations
- Artificial Intelligence — 17 citations into it
- Biomedical Engineering — 17 citations into it; #2,755 of 10,734 by trust here, #4,726 by citations
- Neuroscience — 14 citations into it
Whom Jörn Diedrichsen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- D. V. Van Essen
- Nikolaus Kriegeskorte
- Reza Shadmehr
- Hamed Nili
- R. Fisher
- Sarang C. Joshi
- Robert M. Kelly
- James V. Haxby
- Kendrick Norris Kay
- Simon B. Eickhoff
Who trusts Jörn Diedrichsen overall
- Catherine J. Stoodley
- Xavier Guell
- Jeremy D. Schmahmann
- Nikolaus Kriegeskorte
- Martin N. Hebart
- John D. E. Gabrieli
- Michael A. Lepori
- Michael C. Freund
- Mohamed L. Seghier
- Noam I. Keren
Papers from Jörn Diedrichsen's perspective
Ordered by how strongly the researchers Jörn Diedrichsen 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
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Neural Correlates of Reach Errors (2005) — 653 citations
- Sensory prediction errors drive cerebellum-dependent adaptation of reaching. (2007) — 899 citations
- Principles of sensorimotor learning (2011) — 1,361 citations
- Use-Dependent and Error-Based Learning of Motor Behaviors (2010) — 377 citations
- A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum (2022)
- Functional boundaries in the human cerebellum revealed by a multi-domain task battery (2019) — 623 citations
- Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis (2017) — 330 citations
- Reliability of dissimilarity measures for multi-voxel pattern analysis (2016) — 524 citations
- On the distribution of cross-validated Mahalanobis distances (2016) — 47 citations
- Inferring brain-computational mechanisms with models of activity measurements (2016) — 53 citations
- Imaging the deep cerebellar nuclei: A probabilistic atlas and normalization procedure (2011) — 383 citations
- A probabilistic MR atlas of the human cerebellum (2009) — 1,379 citations
- A spatially unbiased atlas template of the human cerebellum (2006) — 980 citations
- A Cognitive Neuroscience Perspective on Bimanual Coordination and Interference (2004) — 88 citations