Personal information

deep learning, variational inference, representational similarity, machine learning, generative models, disentanglement, transparency, representation learning, latent variable models
France, United Kingdom

Activities

Employment (3)

IARC/WHO: Lyon, FR

2024-03-01 to present | postdoctoral researcher (GEM - Rare cancer genomics team )
Employment
Source: Self-asserted source
Lisa Bonheme

Orange: Lannion, FR

2019-03 to 2019-09 | NLP intern (TGI/DATA-IA)
Employment
Source: Self-asserted source
Lisa Bonheme

Like a Bird: Lyon, FR

2017-04 to 2017-08 | NLP intern
Employment
Source: Self-asserted source
Lisa Bonheme

Education and qualifications (4)

University of Kent: Canterbury, Kent, GB

2019-09 to 2024-02 | PhD (School of computing)
Education
Source: Self-asserted source
Lisa Bonheme

Machine Learning Summer School: Tübingen (virtual), DE

2020-06-28 to 2020-07-10
Qualification
Source: Self-asserted source
Lisa Bonheme

École pour l'Informatique et les Nouvelles Technologies: Le Kremlin-Bicetre, Île-de-France, FR

2014-09 to 2019-08 | Expert en technologies de l'information
Education
Source: Self-asserted source
Lisa Bonheme

Dublin City University: Dublin, IE

2017 to 2018 | year abroad (School of Computing)
Education
Source: Self-asserted source
Lisa Bonheme

Works (5)

Deconstructing deep active inference

arXiv
2023 | Other
EID:

2-s2.0-85163138305

Part of ISSN: 23318422
Contributors: Champion, T.; Grzes, M.; Bonheme, L.; Bowman, H.
Source: Self-asserted source
Lisa Bonheme via Scopus - Elsevier
grade
Preferred source (of 3)‎

Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders

Journal of Machine Learning Resarch
2023-12-30 | Journal article
Part of ISSN: 1532-4435
Source: Self-asserted source
Lisa Bonheme

FONDUE: AN ALGORITHM TO FIND THE OPTIMAL DIMENSIONALITY OF THE LATENT REPRESENTATIONS OF VARIATIONAL AUTOENCODERS

arXiv
2022 | Other
EID:

2-s2.0-85139149731

Part of ISSN: 23318422
Contributors: Bonheme, L.; Grzes, M.
Source: Self-asserted source
Lisa Bonheme via Scopus - Elsevier

How do Variational Autoencoders Learn? Insights from Representational Similarity

arXiv e-prints
2022 | Journal article
EID:

2-s2.0-85130840055

Part of ISSN: 23318422
Source: Self-asserted source
Lisa Bonheme
grade
Preferred source (of 2)‎

SESAM at SemEval-2020 Task 8: Investigating the Relationship between Image and Text in Sentiment Analysis of Memes

Proceedings of the Fourteenth Workshop on Semantic Evaluation
2020-12 | Conference paper
EID:

2-s2.0-85117672553

URI:

https://www.aclweb.org/anthology/2020.semeval-1.102

Source: Self-asserted source
Lisa Bonheme
grade
Preferred source (of 2)‎

Peer review (5 reviews for 3 publications/grants)

Review activity for Neural networks. (1)
Review activity for Science & education. (3)
Review activity for Social network analysis and mining. (1)