Tiziano Zito
Numerical Methods & Scientific Computing · 2008–2020
A researcher in the Science corpus: 4 papers; trusts 12 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Numerical Methods & Scientific Computing — 36 citations into it
- Artificial Intelligence — 28 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Signal Processing — 8 citations into it; #2,787 of 7,572 by trust here, #5,829 by citations
- Cognitive Neuroscience — 7 citations into it
- Statistics and Probability — 7 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it; #9,327 of 21,575 by trust here, #18,266 by citations
- Computational Theory and Mathematics — 5 citations into it
Whom Tiziano Zito trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Aapo Hyvärinen
- Laurenz Wiskott
- Geoffrey E. Hinton
- David L. Donoho
- Terrence J. Sejnowski
- Anthony J. Bell
- Pietro Berkes
- Mathias Franzius
- V. A. Solé
Who trusts Tiziano Zito overall
- Aapo Hyvärinen
- Radim Rehurek
- Henning Sprekeler
- Nitish Srivastava
- Robert A. Legenstein
- Laurenz Wiskott
- Hermanni Hälvä
- Hiroshi Morioka
- Petr Sojka
- Fabian Pedregosa
Papers from Tiziano Zito's perspective
Ordered by how strongly the researchers Tiziano Zito trusts endorse each paper. Same corpus, a different order for every researcher.
- A Fast Learning Algorithm for Deep Belief Nets
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Pattern Recognition and Machine Learning
- GENERATIVE ADVERSARIAL NETS
- An Information-Maximization Approach to Blind Separation and Blind Deconvolution
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- SciPy 1.0: fundamental algorithms for scientific computing in Python (2019) — 33,467 citations
- An extension of slow feature analysis for nonlinear blind source separation (2014) — 76 citations
- Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python (2020) — 1,246 citations
- Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework (2008)