Fabian H Sinz
Cognitive Neuroscience · 2004–2019
A researcher in the Science corpus: 9 papers; trusts 124 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 64 citations into it
- Computer Vision and Pattern Recognition — 61 citations into it
- Artificial Intelligence — 53 citations into it; #15,199 of 35,345 by trust here, #10,798 by citations
- Representation & Self-Supervised Learning — 31 citations into it
- Cellular and Molecular Neuroscience — 30 citations into it
- Model Architectures — 22 citations into it
- Optimization & Training — 21 citations into it
- Neuroscience — 16 citations into it
Whom Fabian H Sinz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Aapo Hyvärinen
- Geoffrey E. Hinton
- Robert Tibshirani
- Alex Krizhevsky
- Yoshua Bengio
- Barbara Olshausen
- Thorsten Joachims
- Vladimir Naumovich Vapni
- Michael S. Lewicki
- H. Barlow
Who trusts Fabian H Sinz overall
- Johannes Ballé
- Takeru Miyato
- Marthinus Christoffel du Plessis
- Jason Aaron Edward Weston
- Olivier Chapelle
- J. Paul Brooks
- Bharath K. Sriperumbudur
- Yang Yu
- Ronan Collobert
- Iro Laina
Papers from Fabian H Sinz's perspective
Ordered by how strongly the researchers Fabian H Sinz 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Trading convexity for scalability (2006) — 407 citations
- Learning Depth from Stereo (2004) — 59 citations
- Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes (2016) — 86 citations
- Engineering a Less Artificial Intelligence. (2019) — 168 citations
- Principles of connectivity among morphologically defined cell types in adult neocortex (2015) — 832 citations
- Population code in mouse V1 facilitates read-out of natural scenes through increased sparseness (2014) — 200 citations
- What Is the Limit of Redundancy Reduction with Divisive Normalization? (2013) — 5 citations
- Lp-Nested Symmetric Distributions (2010) — 20 citations
- Large Scale Transductive SVMs (2006) — 535 citations