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Enhancing Discrete Choice Models with Neural Networks

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin, Brian Alan Tappy-Sifringer
2018
Conference Papers

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Alexandre Massoud Alahi, Virginie Janine Camille Lurkin, Brian Alan Tappy-Sifringer
2018
Conference Papers

Source officielle

Publications associées (29)

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https://infoscience.epfl.ch/entities/publication/47c8a770-535d-4e46-8a01-b8790ac96571

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Publications associées (29)

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Learning to Reason with Neural Networks: Principles and Methods

Aryo Lotfi Jandaghi

This thesis focuses on understanding and improving the reasoning capabilities of neural networks. It develops theoretical results and empirical analyses to uncover reasoning potential and limitations, leveraging these insights to guide the design of improv ...

EPFL2025

Spectroscopy of two-dimensional interacting lattice electrons using symmetry-aware neural backflow transformations

Giuseppe Carleo, Jannes Willy E. Nys, Imelda Romero

Neural networks have shown to be a powerful tool to represent the ground state of quantum many-body systems, including fermionic systems. However, efficiently integrating lattice symmetries into neural representations remains a significant challenge. In th ...

NATURE PORTFOLIO2025

A comparative analysis of gene expression profiling by statistical and machine learning approaches

Anaïs Betsabeh Haget, Maria Boulougouri

Motivation Many machine learning (ML) models developed to classify phenotype from gene expression data provide interpretations for their decisions, with the aim of understanding biological processes. For many models, including neural networks, interpretati ...

OXFORD UNIV PRESS2025