Maystre, Lucas

14 publications

NeurIPS 2025 Incremental Sequence Classification with Temporal Consistency Lucas Maystre, Gabriel Barello, Tudor Berariu, Aleix Cambray, Rares Dolga, Alvaro Ortega Gonzalez, Andrei Cristian Nica, David Barber

TMLR 2025 Unifying Linear-Time Attention via Latent Probabilistic Modelling Rares Dolga, Lucas Maystre, Marius Cobzarenco, David Barber

UAI 2024 Fast Interactive Search Under a Scale-Free Comparison Oracle Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser

TMLR 2024 On the Importance of Uncertainty in Decision-Making with Large Language Models Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek

CLeaR 2023 Estimating Long-Term Causal Effects from Short-Term Experiments and Long-Term Observational Data with Unobserved Confounding Graham Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee

UAI 2022 Multistate Analysis with Infinite Mixtures of Markov Chains Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara

NeurIPS 2022 Temporally-Consistent Survival Analysis Lucas Maystre, Daniel Russo

AISTATS 2021 Collaborative Classification from Noisy Labels Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas

ECML-PKDD 2021 Gaussian Process Encoders: VAEs with Reliable Latent-Space Uncertainty Judith Bütepage, Lucas Maystre, Mounia Lalmas

ICML 2020 Scalable and Efficient Comparison-Based Search Without Features Daniyar Chumbalov, Lucas Maystre, Matthias Grossglauser

ICML 2017 ChoiceRank: Identifying Preferences from Node Traffic in Networks Lucas Maystre, Matthias Grossglauser

ICML 2017 Just Sort It! a Simple and Effective Approach to Active Preference Learning Lucas Maystre, Matthias Grossglauser

ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young-Jun Ko, Lucas Maystre, Matthias Grossglauser

NeurIPS 2015 Fast and Accurate Inference of Plackett–Luce Models Lucas Maystre, Matthias Grossglauser