Julyan Arbel

Orcid: 0000-0002-2525-4416

According to our database1, Julyan Arbel authored at least 24 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits.
CoRR, 2024

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.
CoRR, 2024

2023
Reparameterization of extreme value framework for improved Bayesian workflow.
Comput. Stat. Data Anal., November, 2023

Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review.
CoRR, 2023

Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data.
CoRR, 2023

A Primer on Bayesian Neural Networks: Review and Debates.
CoRR, 2023

The fine print on tempered posteriors.
CoRR, 2023

Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series.
CoRR, 2023

TinyMLOps for real-time ultra-low power MCUs applied to frame-based event classification.
Proceedings of the 3rd Workshop on Machine Learning and Systems, 2023

2022
Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors.
Stat. Comput., 2022

Cold Posteriors through PAC-Bayes.
CoRR, 2022

Imposing Gaussian Pre-Activations in a Neural Network.
CoRR, 2022

2021
Bayesian Inverse Regression for Vascular Magnetic Resonance Fingerprinting.
IEEE Trans. Medical Imaging, 2021

Dirichlet process mixtures under affine transformations of the data.
Comput. Stat., 2021

LDpred2: better, faster, stronger.
Bioinform., 2021

Bayesian neural network unit priors and generalized Weibull-tail property.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
Bayesian nonparametric priors for hidden Markov random fields.
Stat. Comput., 2020

Approximate Bayesian Computation Via the Energy Statistic.
IEEE Access, 2020

2019
Dependence properties and Bayesian inference for asymmetric multivariate copulas.
J. Multivar. Anal., 2019

Quantitative Mri Characterization of Brain Abnormalities in DE NOVO Parkinsonian Patients.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Understanding Priors in Bayesian Neural Networks at the Unit Level.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Bayesian neural networks increasingly sparsify their units with depth.
CoRR, 2018

2017
A moment-matching Ferguson & Klass algorithm.
Stat. Comput., 2017

2016
Full Bayesian inference with hazard mixture models.
Comput. Stat. Data Anal., 2016


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