Simone Severini
Artificial Intelligence · 2004–2019
A researcher in the Science corpus: 7 papers; trusts 9 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 68 citations into it; #25,242 of 35,345 by trust here, #16,166 by citations
- Atomic and Molecular Physics, and Optics — 31 citations into it; #3,715 of 7,135 by trust here, #3,776 by citations
- Probabilistic & Bayesian Methods — 13 citations into it
- Statistical Learning Theory — 7 citations into it
Whom Simone Severini trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Simone Severini overall
Papers from Simone Severini's perspective
Ordered by how strongly the researchers Simone Severini 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)
- GENERATIVE ADVERSARIAL NETS
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Improved Techniques for Training GANs
- Rethinking the Inception Architecture for Computer Vision
- Training Products of Experts by Minimizing Contrastive Divergence
- Information Theory: 1948-1998 - Guest Editorial
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
Their papers
- (Non-)Contextuality of Physical Theories as an Axiom (2010) — 140 citations
- The von Neumann Entropy of Networks (2008) — 117 citations
- A framework to assess the resilience of farming systems (2019) — 657 citations
- Hierarchical quantum classifiers (2018) — 381 citations
- Quantum machine learning: a classical perspective (2017) — 544 citations
- Quantum graphity: A model of emergent locality (2008) — 171 citations
- The Laplacian of a Graph as a Density Matrix: A Basic Combinatorial Approach to Separability of Mixed States (2004) — 187 citations