Laetitia Meng-Papaxanthos

According to our database, Laetitia Meng-Papaxanthos authored at least 16 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

<tt>networkGWAS</tt> : a network-based approach to discover genetic associations.

Giulia Muzio, Leslie O'Bray, Laetitia Meng-Papaxanthos, Juliane Klatt, Krista Fischer, Karsten M. Borgwardt

Bioinform., 2023

LSMMD-MA: scaling multimodal data integration for single-cell genomics data analysis.

Laetitia Meng-Papaxanthos, Ran Zhang, Gang Li, Marco Cuturi, William Stafford Noble, Jean-Philippe Vert

Bioinform., 2023

2022

Software for Large Scale MMD-MA.

Laetitia Meng-Papaxanthos, Ran Zhang, Gang Li, Marco Cuturi, William Stafford Noble, Jean-Philippe Vert

Dataset, January, 2022

Multimodal Single-Cell Translation and Alignment with Semi-Supervised Learning.

Ran Zhang, Laetitia Meng-Papaxanthos, Jean-Philippe Vert, William Stafford Noble

J. Comput. Biol., 2022

Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein.

Marco Cuturi, Laetitia Meng-Papaxanthos, Yingtao Tian, Charlotte Bunne, Geoff Davis, Olivier Teboul

CoRR, 2022

Conditional generative modeling for <i>de novo</i> protein design with hierarchical functions.

Tim Kucera, Matteo Togninalli, Laetitia Meng-Papaxanthos

Bioinform., 2022

Semi-supervised Single-Cell Cross-modality Translation Using Polarbear.

Ran Zhang, Laetitia Meng-Papaxanthos, Jean-Philippe Vert, William Stafford Noble

Proceedings of the Research in Computational Molecular Biology, 2022

Proximal Optimal Transport Modeling of Population Dynamics.

Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

JKOnet: Proximal Optimal Transport Modeling of Population Dynamics.

Charlotte Bunne, Laetitia Meng-Papaxanthos, Andreas Krause, Marco Cuturi

CoRR, 2021

2020

Machine Learning for Interaction Discovery in Genetics and Bioengineering.

Laetitia Papaxanthos

PhD thesis, 2020

2019

CASMAP: detection of statistically significant combinations of SNPs in association mapping.

Felipe Llinares-López, Laetitia Papaxanthos, Damian Roqueiro, Dean A. Bodenham, Karsten M. Borgwardt

Bioinform., 2019

Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings.

Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2017

Genome-wide genetic heterogeneity discovery with categorical covariates.

Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Damian Roqueiro, COPDGene Investigators, Karsten M. Borgwardt

Bioinform., 2017

2016

Finding significant combinations of features in the presence of categorical covariates.

Laetitia Papaxanthos, Felipe Llinares-López, Dean A. Bodenham, Karsten M. Borgwardt

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Searching for significant patterns in stratified data.

Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Karsten M. Borgwardt

CoRR, 2015

Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing.

Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos, Karsten M. Borgwardt

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015