Interference-aware MIMO precoder design with realistic power constraints. - Felipe Llinares-López; Matilde Sánchez Fernández; Emilio Parrado-Hernández; Ana García Armada (ICC Workshops, 2013)

Identifying Higher-order Combinations of Binary Features. - Felipe Llinares; Mahito Sugiyama; Karsten M. Borgwardt (CoRR, 2014)

Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing. - Felipe Llinares-López; Mahito Sugiyama; Laetitia Papaxanthos; Karsten M. Borgwardt (KDD, 2015)

Significant Subgraph Mining with Multiple Testing Correction. - Mahito Sugiyama; Felipe Llinares-López; Niklas Kasenburg; Karsten M. Borgwardt (SDM, 2015)

Genome-wide detection of intervals of genetic heterogeneity associated with complex traits. - Felipe Llinares-López; Dominik G. Grimm; Dean A. Bodenham; Udo Gieraths; Mahito Sugiyama; Beth Rowan; Karsten M. Borgwardt (Bioinform., 2015)

Searching for significant patterns in stratified data. - Felipe Llinares-López; Laetitia Papaxanthos; Dean A. Bodenham; Karsten M. Borgwardt (CoRR, 2015)

Finding significant combinations of features in the presence of categorical covariates. - Laetitia Papaxanthos; Felipe Llinares-López; Dean A. Bodenham; Karsten M. Borgwardt (NIPS, 2016)

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)

graphkernels: R and Python packages for graph comparison. - Mahito Sugiyama; M. Elisabetta Ghisu; Felipe Llinares-López; Karsten M. Borgwardt (Bioinform., 2018)

Wasserstein Weisfeiler-Lehman Graph Kernels. - Matteo Togninalli; M. Elisabetta Ghisu; Felipe Llinares-López; Bastian Rieck; Karsten M. Borgwardt (NeurIPS, 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)

Graph Kernels: State-of-the-Art and Future Challenges. - Karsten M. Borgwardt; M. Elisabetta Ghisu; Felipe Llinares-López; Leslie O'Bray; Bastian Rieck (Found. Trends Mach. Learn., 2020)

Efficient and Modular Implicit Differentiation. - Mathieu Blondel; Quentin Berthet; Marco Cuturi; Roy Frostig; Stephan Hoyer; Felipe Llinares-López; Fabian Pedregosa; Jean-Philippe Vert (NeurIPS, 2022)

Learning Energy Networks with Generalized Fenchel-Young Losses. - Mathieu Blondel; Felipe Llinares-López; Robert Dadashi; Léonard Hussenot; Matthieu Geist (NeurIPS, 2022)

Differentiable Clustering with Perturbed Spanning Forests. - Lawrence Stewart; Francis R. Bach; Felipe Llinares-López; Quentin Berthet (NeurIPS, 2023)

Decoding-time Realignment of Language Models. - Tianlin Liu; Shangmin Guo; Leonardo Bianco; Daniele Calandriello; Quentin Berthet; Felipe Llinares-López; Jessica Hoffmann; Lucas Dixon; Michal Valko; Mathieu Blondel (ICML, 2024)

Direct Language Model Alignment from Online AI Feedback. - Shangmin Guo; Biao Zhang; Tianlin Liu; Tianqi Liu 002; Misha Khalman; Felipe Llinares; Alexandre Ramé; Thomas Mesnard; Yao Zhao; Bilal Piot; Johan Ferret; Mathieu Blondel (CoRR, 2024)

Implicit Diffusion: Efficient optimization through stochastic sampling. - Pierre Marion; Anna Korba; Peter L. Bartlett; Mathieu Blondel; Valentin De Bortoli; Arnaud Doucet; Felipe Llinares-López; Courtney Paquette; Quentin Berthet (AISTATS, 2025)