Julyan Arbel

According to our database, Julyan Arbel authored at least 30 papers between 2016 and 2024.

Collaborative distances:

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

2024

Shrinkage for extreme partial least-squares.

Julyan Arbel, Stéphane Girard, Hadrien Lorenzo

Stat. Comput., December, 2024

Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms.

Daria Bystrova, Charles K. Assaad, Julyan Arbel, Emilie Devijver, Éric Gaussier, Wilfried Thuiller

Trans. Mach. Learn. Res., 2024

Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit.

Julien Zhou, Pierre Gaillard, Thibaud Rahier, Julyan Arbel

CoRR, 2024

Just rotate it! Uncertainty estimation in closed-source models via multiple queries.

Konstantinos Pitas, Julyan Arbel

CoRR, 2024

Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits.

Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel

CoRR, 2024

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

CoRR, 2024

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Reparameterization of extreme value framework for improved Bayesian workflow.

Théo Moins, Julyan Arbel, Stéphane Girard, Anne Dutfoy

Comput. Stat. Data Anal., November, 2023

Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review.

Minh Tri Le, Pierre Wolinski, Julyan Arbel

CoRR, 2023

Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data.

Konstantinos Pitas, Julyan Arbel

CoRR, 2023

A Primer on Bayesian Neural Networks: Review and Debates.

Julyan Arbel, Konstantinos Pitas, Mariia Vladimirova, Vincent Fortuin

CoRR, 2023

Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series.

Charles K. Assaad, Daria Bystrova, Julyan Arbel, Emilie Devijver, Éric Gaussier, Wilfried Thuiller

CoRR, 2023

Regularization for Hybrid N-Bit Weight Quantization of Neural Networks on Ultra-Low Power Microcontrollers.

Minh Tri Le, Etienne de Foras, Julyan Arbel

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

TinyMLOps for real-time ultra-low power MCUs applied to frame-based event classification.

Minh Tri Le, Julyan Arbel

Proceedings of the 3rd Workshop on Machine Learning and Systems, 2023

The Fine Print on Tempered Posteriors.

Konstantinos Pitas, Julyan Arbel

Proceedings of the Asian Conference on Machine Learning, 2023

2022

Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors.

Florence Forbes, Hien Duy Nguyen, TrungTin Nguyen, Julyan Arbel

Stat. Comput., 2022

Cold Posteriors through PAC-Bayes.

Konstantinos Pitas, Julyan Arbel

CoRR, 2022

Imposing Gaussian Pre-Activations in a Neural Network.

Pierre Wolinski, Julyan Arbel

CoRR, 2022

2021

Bayesian Inverse Regression for Vascular Magnetic Resonance Fingerprinting.

Fabien Boux, Florence Forbes, Julyan Arbel, Benjamin Lemasson, Emmanuel Luc Barbier

IEEE Trans. Medical Imaging, 2021

Dirichlet process mixtures under affine transformations of the data.

Julyan Arbel, Riccardo Corradin, Bernardo Nipoti

Comput. Stat., 2021

LDpred2: better, faster, stronger.

Florian Privé, Julyan Arbel, Bjarni J. Vilhjálmsson

Bioinform., 2021

Bayesian neural network unit priors and generalized Weibull-tail property.

Mariia Vladimirova, Julyan Arbel, Stéphane Girard

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Bayesian nonparametric priors for hidden Markov random fields.

Hongliang Lü, Julyan Arbel, Florence Forbes

Stat. Comput., 2020

Approximate Bayesian Computation Via the Energy Statistic.

Hien Duy Nguyen, Julyan Arbel, Hongliang Lü, Florence Forbes

IEEE Access, 2020

2019

Dependence properties and Bayesian inference for asymmetric multivariate copulas.

Julyan Arbel, Marta Crispino, Stéphane Girard

J. Multivar. Anal., 2019

Quantitative Mri Characterization of Brain Abnormalities in DE NOVO Parkinsonian Patients.

Verónica Muñoz Ramírez, Florence Forbes, Julyan Arbel, Alexis Arnaud, Michel Dojat

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Understanding Priors in Bayesian Neural Networks at the Unit Level.

Mariia Vladimirova, Jakob Verbeek, Pablo Mesejo, Julyan Arbel

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Bayesian neural networks increasingly sparsify their units with depth.

Mariia Vladimirova, Julyan Arbel, Pablo Mesejo

CoRR, 2018

2017

A moment-matching Ferguson & Klass algorithm.

Julyan Arbel, Igor Prünster

Stat. Comput., 2017

2016

Full Bayesian inference with hazard mixture models.

Julyan Arbel, Antonio Lijoi, Bernardo Nipoti

Comput. Stat. Data Anal., 2016