Fabio Anselmi

According to our database, Fabio Anselmi authored at least 31 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Perceptual misalignment of texture representations in convolutional neural networks.

Ludovica de Paolis, Fabio Anselmi, Alessio Ansuini, Eugenio Piasini

CoRR, April, 2026

Local search, semantics, and genetic programming: a global analysis.

Fabio Anselmi, Mauro Castelli, Alberto d'Onofrio, Luca Manzoni, Luca Mariot, Martina Saletta

Soft Comput., March, 2026

Implicit bias as a Gauge correction: Theory and Inverse Design.

Nicola Aladrah, Emanuele Ballarin, Matteo Biagetti, Alessio Ansuini, Alberto d'Onofrio, Fabio Anselmi

CoRR, January, 2026

The Interplay Between Non-Instantaneous Dynamics of mRNA and Bounded Extrinsic Stochastic Perturbations for a Self-Enhancing Transcription Factor.

Lorenzo Cabriel, Giulio Caravagna, Sebastiano de Franciscis, Fabio Anselmi, Alberto d'Onofrio

Entropy, 2026

2025

Increasing the quantum tunneling probability through a learned ancilla-assisted protocol.

Renzo Testa, Alejandro Rodriguez-Garcia, Alberto d'Onofrio, Andrea Trombettoni, Fabio Benatti, Fabio Anselmi

Quantum Mach. Intell., December, 2025

The Spectral Bias of Shallow Neural Network Learning is Shaped by the Choice of Non-linearity.

Justin Sahs, Ryan Pyle, Fabio Anselmi, Ankit B. Patel

CoRR, March, 2025

Driving enhanced exciton transfer by automatic differentiation.

Emanuele Ballarin, Diana A. Chisholm, Andrea Smirne, M. Paternostro, Fabio Anselmi, S. Donadi

Mach. Learn. Sci. Technol., 2025

Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias.

Lorenzo Basile, Nikos Karantzas, Alberto d'Onofrio, Luca Manzoni, Luca Bortolussi, Alex Rodriguez, Fabio Anselmi

Proceedings of the International Joint Conference on Neural Networks, 2025

Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations.

Lorenzo Basile, Santiago Acevedo, Luca Bortolussi, Fabio Anselmi, Alex Rodriguez

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples.

Josue Ortega Caro, Yilong Ju, Ryan Pyle, Sourav Dey, Wieland Brendel, Fabio Anselmi, Ankit B. Patel

Frontiers Comput. Neurosci., 2024

Editorial: Symmetry as a guiding principle in artificial and brain neural networks, volume II.

Fabio Anselmi, Ankit B. Patel

Frontiers Comput. Neurosci., 2024

2023

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing.

Lucrezia Patruno, Salvatore Milite, Riccardo Bergamin, Nicola Calonaci, Alberto d'Onofrio, Fabio Anselmi, Marco Antoniotti, Alex Graudenzi, Giulio Caravagna

PLoS Comput. Biol., November, 2023

Generative abstraction of Markov population processes.

Francesca Cairoli, Fabio Anselmi, Alberto d'Onofrio, Luca Bortolussi

Theor. Comput. Sci., October, 2023

Robust deep learning object recognition models rely on low frequency information in natural images.

Zhe Li, Josue Ortega Caro, Evgenia Rusak, Wieland Brendel, Matthias Bethge, Fabio Anselmi, Ankit B. Patel, Andreas S. Tolias, Xaq Pitkow

PLoS Comput. Biol., March, 2023

Relating Implicit Bias and Adversarial Attacks through Intrinsic Dimension.

Lorenzo Basile, Nikos Karantzas, Alberto d'Onofrio, Luca Bortolussi, Alex Rodriguez, Fabio Anselmi

CoRR, 2023

Data Symmetries and Learning in Fully Connected Neural Networks.

Fabio Anselmi, Luca Manzoni, Alberto d'Onofrio, Alex Rodriguez, Giulio Caravagna, Luca Bortolussi, Francesca Cairoli

IEEE Access, 2023

2022

Shallow Univariate ReLU Networks as Splines: Initialization, Loss Surface, Hessian, and Gradient Flow Dynamics.

Justin Sahs, Ryan Pyle, Aneel Damaraju, Josue Ortega Caro, Onur Tavaslioglu, Andy Lu, Fabio Anselmi, Ankit B. Patel

Frontiers Artif. Intell., 2022

Understanding Robustness and Generalization of Artificial Neural Networks Through Fourier Masks.

Nikos Karantzas, Emma Besier, Josue Ortega Caro, Xaq Pitkow, Andreas S. Tolias, Ankit B. Patel, Fabio Anselmi

Frontiers Artif. Intell., 2022

Editorial: Symmetry as a guiding principle in artificial and brain neural networks.

Fabio Anselmi, Ankit B. Patel

Frontiers Comput. Neurosci., 2022

Machine learning algorithms on eye tracking trajectories to classify patients with spatial neglect.

Benedetta Franceschiello, Tommaso Di Noto, Alexia Bourgeois, Micah M. Murray, Astrid Minier, Pierre Pouget, Jonas Richiardi, Paolo Bartolomeo, Fabio Anselmi

Comput. Methods Programs Biomed., 2022

Representation Learning in Sensory Cortex: A Theory.

Fabio Anselmi, Tomaso A. Poggio

IEEE Access, 2022

2020

A computational model for grid maps in neural populations.

Fabio Anselmi, Micah M. Murray, Benedetta Franceschiello

J. Comput. Neurosci., 2020

2019

Symmetry-adapted representation learning.

Fabio Anselmi, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio

Pattern Recognit., 2019

A computational model for grid maps in neural populations.

Fabio Anselmi, Benedetta Franceschiello, Micah M. Murray, Lorenzo Rosasco

CoRR, 2019

Genuine Personality Recognition from Highly Constrained Face Images.

Fabio Anselmi, Nicoletta Noceti, Lorenzo Rosasco, Robert Ward

Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019

2016

Unsupervised learning of invariant representations.

Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio

Theor. Comput. Sci., 2016

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation.

Joel Z. Leibo, Qianli Liao, Winrich Freiwald, Fabio Anselmi, Tomaso A. Poggio

CoRR, 2016

2015

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex.

Joel Z. Leibo, Qianli Liao, Fabio Anselmi, Tomaso A. Poggio

PLoS Comput. Biol., 2015

Deep Convolutional Networks are Hierarchical Kernel Machines.

Fabio Anselmi, Lorenzo Rosasco, Cheston Tan, Tomaso A. Poggio

CoRR, 2015

On Invariance and Selectivity in Representation Learning.

Fabio Anselmi, Lorenzo Rosasco, Tomaso A. Poggio

CoRR, 2015

2013

Unsupervised Learning of Invariant Representations in Hierarchical Architectures.

Fabio Anselmi, Joel Z. Leibo, Lorenzo Rosasco, Jim Mutch, Andrea Tacchetti, Tomaso A. Poggio

CoRR, 2013