41 citations
- University of FlorenceIT34 papers
- Fermi National Accelerator LaboratoryUS31 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di PisaIT31 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT31 papers
- University of California, DavisUS31 papers
- Boston UniversityUS30 papers
- Brown UniversityUS30 papers
- California Institute of TechnologyUS30 papers
- Frascati ScienzaIT30 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT30 papers
- Naples Anesthesia & Physician AssociatesUS30 papers
- Northwestern UniversityUS30 papers
8 papers · 1 filter
Embedding of FRPN in CNN architecture
Alberto Rossi, Markus Hagenbuchner, Franco Scarselli +1
This paper extends the fully recursive perceptron network (FRPN) model for vectorial inputs to include deep convolutional neural networks (CNNs) which can accept multi-dimensional…
Nonlinear nonholonomic constraints
Federico Talamucci
One of the founders of the mechanics of nonoholonomic systems is Voronec who published in 1901 a significant generalization of the Caplygin's equations, by removing some restrictiv…
Jointly Learning to Detect Emotions and Predict Facebook Reactions
Lisa Graziani, Stefano Melacci, Marco Gori
The growing ubiquity of Social Media data offers an attractive perspective for improving the quality of machine learning-based models in several fields, ranging from Computer Visio…
Spatiotemporal Local Propagation
Alessandro Betti, Marco Gori
This paper proposes an in-depth re-thinking of neural computation that parallels apparently unrelated laws of physics, that are formulated in the variational framework of the least…
Modular specification of monads through higher-order presentations
Benedikt Ahrens, André Hirschowitz, Ambroise Lafont +1
In their work on second-order equational logic, Fiore and Hur have studied presentations of simply typed languages by generating binding constructions and equations among them. To…
Fix Your Features: Stationary and Maximally Discriminative Embeddings using Regular Polytope (Fixed Classifier) Networks
Federico Pernici, Matteo Bruni, Claudio Baecchi +1
Neural networks are widely used as a model for classification in a large variety of tasks. Typically, a learnable transformation (i.e. the classifier) is placed at the end of such…