Edoardo Vecchi

eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems

I. Horenko, T. O'Kane, Edoardo Vecchi, 2022, Neural Computation.

Low-Cost Probabilistic 3D Denoising with Applications for Ultra-Low-Radiation Computed Tomography

I. Horenko, A. Stroh, S. Gerber, 2022, J. Imaging.

On cheap entropy-sparsified regression learning

I. Horenko, A. Wächter, O. Schenk, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography

I. Horenko, A. Stroh, S. Gerber, 2021, bioRxiv.

Entropic approximate learning for financial decision-making in the small data regime

I. Horenko, P. Gagliardini, Edoardo Vecchi, 2023, Research in International Business and Finance.

Gauge-optimal approximate learning for small data classification problems

I. Horenko, Edoardo Vecchi, Davide Bassetti, 2023, ArXiv.

Spiking neural networks provide accurate, efficient and robust models for whisker stimulus classification and allow for inter-individual generalization

Maik C. Stüttgen, I. Horenko, H. Luhmann, 2023, bioRxiv.

Gauge-Optimal Approximate Learning for Small Data Classification

I. Horenko, Edoardo Vecchi, Davide Bassetti, 2023, Neural Computation.