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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

Official source

Related publications (29)

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

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Related publications (29)

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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 ...

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

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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 ...

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

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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 ...

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