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Number of documents

87

Julyan Arbel


You can find:

- my webpage: http://www.julyanarbel.com/

- my CV in English and in French.


Journal articles24 documents

  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. Discussion of the paper "Rank-Normalization, Folding, and Localization: An Improved $\widehat{R}$ for Assessing Convergence of MCMC''. Bayesian Analysis, International Society for Bayesian Analysis, 2021, 16 (2), pp.711--712. ⟨10.1214/20-ba1221⟩. ⟨hal-03222934⟩
  • Fabien Boux, Florence Forbes, Julyan Arbel, Benjamin Lemasson, Emmanuel L. Barbier. Bayesian inverse regression for vascular magnetic resonance fingerprinting. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2021, 40 (7), pp.1827-1837. ⟨10.1109/TMI.2021.3066781⟩. ⟨hal-02314026v3⟩
  • Julyan Arbel, Riccardo Corradin, Bernardo Nipoti. Dirichlet process mixtures under affine transformations of the data. Computational Statistics, Springer Verlag, 2021, 36, pp.577-601. ⟨10.1007/s00180-020-01013-y⟩. ⟨hal-01950652v2⟩
  • Giovanni Poggiato, Tamara Münkemüller, Daria Bystrova, Julyan Arbel, James Clark, et al.. On the interpretations of joint modelling in community ecology. Trends in Ecology and Evolution, Elsevier, 2021, 36 (5), pp.391-401. ⟨10.1016/j.tree.2021.01.002⟩. ⟨hal-03153558⟩
  • Daria Bystrova, Giovanni Poggiato, Billur Bektaş, Julyan Arbel, James S Clark, et al.. Clustering species with residual covariance matrix in Joint Species Distribution models. Frontiers in Ecology and Evolution, Frontiers Media S.A, 2021, 9, pp.601384:1-11. ⟨10.3389/fevo.2021.601384⟩. ⟨hal-03151472⟩
  • Julyan Arbel, Guillaume Kon Kam King, Antonio Lijoi, Luis E. Nieto‐Barajas, Igor Prünster. BNPdensity: Bayesian nonparametric mixture modelling in R. Australian and New Zealand Journal of Statistics, Wiley, In press, pp.28. ⟨10.1111/anzs.12342⟩. ⟨hal-03433254⟩
  • Julyan Arbel, Stefano Favaro. Approximating predictive probabilities of Gibbs-type priors. Sankhya A, Springer Verlag, 2021, 83, pp.496-519. ⟨10.1007/s13171-019-00187-y⟩. ⟨hal-01693333⟩
  • Hien D Nguyen, Julyan Arbel, Hongliang Lu, Florence Forbes. Approximate Bayesian computation via the energy statistic. IEEE Access, IEEE, 2020, 8, pp.131683-131698. ⟨10.1109/access.2020.3009878⟩. ⟨hal-02399934⟩
  • Florian Privé, Julyan Arbel, Bjarni J Vilhjálmsson. LDpred2: better, faster, stronger. Bioinformatics, Oxford University Press (OUP), 2020, 36 (22-23), pp.5424-5431. ⟨10.1093/bioinformatics/btaa1029⟩. ⟨hal-03132949⟩
  • Julyan Arbel, Olivier Marchal, Hien T Nguyen. On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables. ESAIM: Probability and Statistics, EDP Sciences, 2020, 24, pp.39-55. ⟨10.1051/ps/2019018⟩. ⟨hal-01998252⟩
  • Hongliang Lu, Julyan Arbel, Florence Forbes. Bayesian nonparametric priors for hidden Markov random fields. Statistics and Computing, Springer Verlag (Germany), 2020, 30, pp.1015-1035. ⟨10.1007/s11222-020-09935-9⟩. ⟨hal-02163046v3⟩
  • Mariia Vladimirova, Stéphane Girard, Hien Nguyen, Julyan Arbel. Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions. Stat, John Wiley & Sons, 2020, 9 (1), pp.e318:1-8. ⟨10.1002/sta4.318⟩. ⟨hal-02545121v2⟩
  • Julyan Arbel, Olivier Marchal, Bernardo Nipoti. On the Hurwitz zeta function with an application to the exponential-beta distribution. Journal of Inequalities and Applications, SpringerOpen, 2020, 2020, pp.89:1-8. ⟨10.1186/s13660-020-02357-1⟩. ⟨hal-02400451⟩
  • Julyan Arbel, Pierpaolo de Blasi, Igor Prünster. Stochastic approximations to the Pitman-Yor process. Bayesian Analysis, International Society for Bayesian Analysis, 2019, 14 (3), pp.753-771. ⟨10.1214/18-BA1127⟩. ⟨hal-01950654⟩
  • Caroline Lawless, Julyan Arbel. A simple proof of Pitman-Yor's Chinese restaurant process from its stick-breaking representation. Dependence Modeling, De Gruyter, 2019, 7 (1), pp.45-52. ⟨10.1515/demo-2019-0003⟩. ⟨hal-01950653⟩
  • Julyan Arbel, Marta Crispino, Stéphane Girard. Dependence properties and Bayesian inference for asymmetric multivariate copulas. Journal of Multivariate Analysis, Elsevier, 2019, 174, pp.104530:1-20. ⟨10.1016/j.jmva.2019.06.008⟩. ⟨hal-01963975v2⟩
  • Julyan Arbel, Stefano Favaro, Bernardo Nipoti, Yee Whye Teh. Bayesian nonparametric inference for discovery probabilities: credible intervals and large sample asymptotics. Statistica Sinica, Taipei : Institute of Statistical Science, Academia Sinica, 2017, 27, pp.839-858. ⟨10.5705/ss.202015.0250⟩. ⟨hal-01203324⟩
  • Julyan Arbel, Igor Prünster. A moment-matching Ferguson & Klass algorithm. Statistics and Computing, Springer Verlag (Germany), 2017, 27 (1), pp.3-17. ⟨10.1007/s11222-016-9676-8⟩. ⟨hal-01396587⟩
  • Julyan Arbel, Vianney Costemalle. Estimation des flux d’immigration : réconciliation de deux sources par une approche bayésienne. Economie et Statistique / Economics and Statistics, INSEE, 2016, 483-484-485, pp.121-149. ⟨hal-01396606⟩
  • Julyan Arbel, Antonio Lijoi, Bernardo Nipoti. Full Bayesian inference with hazard mixture models. Computational Statistics and Data Analysis, Elsevier, 2016, 93, pp.359--372. ⟨10.1016/j.csda.2014.12.003⟩. ⟨hal-01203296⟩
  • Julyan Arbel, Kerrie L. Mengersen, Judith Rousseau. Bayesian nonparametric dependent model for partially replicated data: the influence of fuel spills on species diversity . Annals of Applied Statistics, Institute of Mathematical Statistics, 2016, 10 (3), pp.1496-1516. ⟨10.1214/16-AOAS944⟩. ⟨hal-01203345⟩
  • Julyan Arbel, Catherine K King, Ben Raymond, Tristrom Winsley, Kerrie L. Mengersen. Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel-contaminated soil . Ecology and Evolution, Wiley Open Access, 2015, ⟨10.1002/ece3.1493⟩. ⟨hal-01203289⟩
  • Julyan Arbel, Igor Prünster. Discussion of Sequential quasi Monte Carlo. Journal of the Royal Statistical Society: Series B, Royal Statistical Society, 2015, 77 (3), pp.559-560. ⟨10.1111/rssb.12104⟩. ⟨hal-01970234⟩
  • Julyan Arbel, Ghislaine Gayraud, Judith Rousseau. Bayesian optimal adaptive estimation using a sieve prior. Scandinavian Journal of Statistics, Wiley, 2013, ⟨10.1002/sjos.12002⟩. ⟨hal-01203280⟩

Conference papers38 documents

  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. On the use of a local R-hat to improve MCMC convergence diagnostic. Energy Forecasting Innovation Conference 2022, May 2022, Londres, United Kingdom. ⟨hal-03683896⟩
  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. A local version of R-hat for MCMC convergence diagnostic. SFdS 2022 - 53èmes Journées de Statistique de la Société Française de Statistique, Jun 2022, Lyon, France. pp.1-6. ⟨hal-03683927⟩
  • Florence Forbes, Hien Duy Nguyen, Trungtin Nguyen, Julyan Arbel. Mixture of expert posterior surrogates for approximate Bayesian computation. SFdS 2022 - 53èmes Journées de Statistique de la Société Française de Statistique, Jun 2022, Lyon, France. pp.1-6. ⟨hal-03679688⟩
  • Julyan Arbel, Florence Forbes, Hien Duy Nguyen, Trungtin Nguyen. Approximate Bayesian computation with surrogate posteriors. ISBA 2021 - World Meeting of the International Society for Bayesian Analysis, Jun 2021, Marseille, France. ⟨hal-03337949⟩
  • Julyan Arbel, Mario Beraha, Daria Bystrova. Bayesian block-diagonal graphical models via the Fiedler prior. SFdS - 52 Journées de Statistique de la Société Francaise de Statistique, Jun 2021, Nice, France. pp.1-6. ⟨hal-03275245⟩
  • Mariia Vladimirova, Julyan Arbel, Stéphane Girard. Dependence between Bayesian neural network units. BDL 2021 - Workshop. Bayesian Deep Learning NeurIPS, Dec 2021, Montreal, Canada. pp.1-9. ⟨hal-03449211⟩
  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. A Bayesian Framework for Poisson Process Characterization of Extremes with Objective Prior. ISBA 2021 - World Meeting of the International Society for Bayesian Analysis, Jun 2021, Virtual, France. ⟨hal-03347871⟩
  • Mariia Vladimirova, Julyan Arbel, Stéphane Girard. Generalized Weibull-tail distributions. JDS 2021 - 52èmes Journées de Statistique de la Société Française de Statistique (SFdS), Jun 2021, Nice, France. pp.1-6. ⟨hal-03264446⟩
  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. On Reparameterisations of the Poisson Process Model for Extremes in a Bayesian Framework. JDS 2021 - 52èmes Journées de Statistique de la Société Française de Statistique (SFdS), Jun 2021, Nice / Virtual, France. pp.1-6. ⟨hal-03264261⟩
  • Daria Bystrova, Julyan Arbel, Guillaume Kon Kam King, François Deslandes. Approximating the clusters' prior distribution in Bayesian nonparametric models. AABI 2020 - 3rd Symposium on Advances in Approximate Bayesian Inference, Jan 2021, Online, United States. pp.1-16. ⟨hal-03151483⟩
  • Mariia Vladimirova, Julyan Arbel, Stéphane Girard. Bayesian neural network unit priors and generalized Weibull-tail property. ACML 2021 - 13th Asian Conference on Machine Learning, Nov 2021, Virtual, Unknown Region. pp.1-16. ⟨hal-03368522⟩
  • Julyan Arbel, Stéphane Girard, Théo Moins, Anne Dutfoy, Khalil Leachouri. Improving MCMC convergence diagnostic with a local version of R-hat. MAS 2021 - Journées Modélisation Aléatoire et Statistique, Aug 2021, Orléans, France. ⟨hal-03337454⟩
  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. A Bayesian framework for Poisson process characterization of extremes with uninformative prior. CMStatistics 2021 - 14th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2021, London, United Kingdom. ⟨hal-03501794⟩
  • Fabien Boux, Florence Forbes, Julyan Arbel, Aurélien Delphin, Thomas Christen, et al.. Dictionary-based Learning in MR Fingerprinting: Statistical Learning versus Deep Learning. ISMRM 2020 - International Society for Magnetic Resonance in Medicine, Aug 2020, Sidney, Australia. pp.1-4. ⟨hal-02922858⟩
  • Fabien Boux, Florence Forbes, Julyan Arbel, Emmanuel Barbier. Estimation de paramètres IRM en grande dimension via une régression inverse. SFRMBM 2020 - 4e congrés de la Société Française de Résonance Magnétique en Biologie et Médecine, Mar 2020, Strasbourg, France. pp.1. ⟨hal-02428679⟩
  • Marta Crispino, Stéphane Girard, Julyan Arbel. Dependence properties and Bayesian inference for asymmetric multivariate copulas. CMStatistics 2019 - 12th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2019, London, United Kingdom. ⟨hal-02413948⟩
  • Fabien Boux, Florence Forbes, Julyan Arbel, Emmanuel Barbier. Dictionary learning via regression: vascular MRI application. CNIV 2019 - 3e Congrès National d’Imagerie du Vivant, Feb 2019, Paris, France. pp.1-12. ⟨hal-02428647⟩
  • Mariia Vladimirova, Jakob Verbeek, Pablo Mesejo, Julyan Arbel. Understanding Priors in Bayesian Neural Networks at the Unit Level. ICML 2019 - 36th International Conference on Machine Learning, Jun 2019, Long Beach, United States. pp.6458-6467. ⟨hal-02177151⟩
  • Verónica Muñoz Ramírez, Florence Forbes, Julyan Arbel, Alexis Arnaud, Michel Dojat. Quantitative MRI characterization of brain abnormalities in de novo Parkinsonian patients. ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Apr 2019, Venice, Italy. pp.1-4, ⟨10.1109/ISBI.2019.8759544⟩. ⟨hal-01970682v2⟩
  • Mariia Vladimirova, Julyan Arbel, Pablo Mesejo. Bayesian neural network priors at the level of units. AABI 2018 - 1st Symposium on Advances in Approximate Bayesian Inference, Dec 2018, Montréal, Canada. pp.1-6. ⟨hal-01950659⟩
  • Florence Forbes, Hongliang Lu, Julyan Arbel. Non parametric Bayesian priors for hidden Markov random fields: application to image segmentation. BNPSI 2018 : Workshop on Bayesian non parametrics for signal and image processing, Jul 2018, Bordeaux, France. ⟨hal-01941687⟩
  • Hongliang Lu, Julyan Arbel, Florence Forbes. Bayesian Nonparametric Priors for Hidden Markov Random Fields. 50e Journées de la Statistique de la SFdS, May 2018, Saclay, France. pp.1-5. ⟨hal-01941638⟩
  • Mariia Vladimirova, Julyan Arbel, Pablo Mesejo. Bayesian neural networks become heavier-tailed with depth. NeurIPS 2018 - Thirty-second Conference on Neural Information Processing Systems, Dec 2018, Montréal, Canada. pp.1-7. ⟨hal-01950658⟩
  • Julyan Arbel. Introduction to Bayesian nonparametric statistics. Séminaire de Statistique au sommet de Rochebrune, Mar 2018, Megève, France. ⟨hal-01950668⟩
  • Fabien Boux, Florence Forbes, Julyan Arbel, Emmanuel L. Barbier. Dictionary-Free MR Fingerprinting Parameter Estimation Via Inverse Regression. Joint Annual Meeting ISMRM-ESMRMB 2018, Jun 2018, Paris, France. pp.1-2. ⟨hal-01941630⟩
  • Florence Forbes, Hongliang Lu, Julyan Arbel. Non parametric Bayesian priors for hidden Markov random fields. JSM 2018 - Joint Statistical Meeting, Jul 2018, Vancouver, Canada. pp.1-38. ⟨hal-01941679⟩
  • Julyan Arbel, Guillaume Kon Kam King, Igor Prünster. A Bayesian Nonparametric Approach to Ecological Risk Assessment. SMPGD 2018 - Workshop on Statistical Methods for Post Genomic Data, Jan 2018, Montpellier, France. ⟨hal-01950669⟩
  • Julyan Arbel. Some distributional properties of Bayesian neural networks. Workshop on Bayesian nonparametrics, Jul 2018, Bordeaux, France. ⟨hal-01950667⟩
  • Julyan Arbel. Probabilités de découverte d'espèces: Bayes à la rescousse de Good & Turing. Journées Scientifiques d'Inria, Jun 2017, Sophia Antipolis, France. ⟨hal-01667788⟩
  • Julyan Arbel. Bayesian nonparametric mixture models and clustering. Workshop 'New challenges in statistics for social sciences', Oct 2017, Venise, Italy. ⟨hal-01667755⟩
  • Julyan Arbel. Bayesian nonparametric inference for discovery probabilities. YES VIII Workshop on Uncertainty Quantification, Jan 2017, Eindhoven, Netherlands. ⟨hal-01667794⟩
  • Julyan Arbel. Investigating predictive probabilities of Gibbs-type priors. Mathematical Methods of Modern Statistics, Jul 2017, Marseille, France. ⟨hal-01667765⟩
  • Julyan Arbel, Didier Fraix-Burnet, Stéphane Girard. Les écoles d'astrostatistique " Statistics for Astrophysics ". CFIES 2017 - 5ème Colloque Francophone International sur l’Enseignement de la Statistique, Sep 2017, Grenoble, France. ⟨hal-01583854⟩
  • Julyan Arbel. Bayesian nonparametric clustering. School of Statistics for Astrophysics: Bayesian methodology, Oct 2017, Autrans, France. ⟨hal-01667760⟩
  • Julyan Arbel. Approximating predictive probabilities of Gibbs-type priors. ERCIM - 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2017, London, United Kingdom. ⟨hal-01667746⟩
  • Julyan Arbel, Jean-Bernard Salomond. Sequential Quasi Monte Carlo for Dirichlet Process Mixture Models. NIPS - Conference on Neural Information Processing Systems, Dec 2016, Barcelone, Spain. ⟨hal-01405568⟩
  • Julyan Arbel. Truncation error of a superposed gamma process in a decreasing order representation. NIPS Meeting, Dec 2016, Barcelone, Spain. ⟨hal-01667804⟩
  • Julyan Arbel, Kerrie L. Mengersen, Judith Rousseau. On diversity under a Bayesian nonparametric dependent model. XLVII Meeting of the Italian Statistical Society, Italian Statistical Society, Jun 2014, Cagliari, Italy. ⟨hal-01203340⟩

Poster communications9 documents

  • Hongliang Lu, Florence Forbes, Julyan Arbel. Bayesian Nonparametric Priors for Graph Structured Data: Application to Image Segmentation. Bayes Comp 2020, Jan 2020, Gainesville, United States. ⟨hal-02423642⟩
  • Olivier Marchal, Julyan Arbel. Beta and Dirichlet sub-Gaussianity. Bayesian learning theory for complex data modelling Workshop, Sep 2018, Grenoble, France. ⟨hal-01950665⟩
  • Hongliang Lu, Julyan Arbel, Florence Forbes. Bayesian Nonparametric Priors for Hidden Markov Random Fields: Application to Image Segmentation. IFSS 2018 - 2nd Italian-French Statistics Seminar, Sep 2018, Grenoble, France. pp.1. ⟨hal-01950666⟩
  • Aleksandra Malkova, Julyan Arbel, Maria Laura Delle Monache. DATASAFE: understanding Data Accidents for TrAffic SAFEty Acknowledgments. Bayesian learning theory for complex data modelling Workshop, Sep 2018, Grenoble, France. pp.1. ⟨hal-01950663⟩
  • Julyan Arbel. Bayesian Nonparametric Mixtures Why and How?. IFSS 2018 - 2nd Italian-French Statistics Seminar, Sep 2018, Grenoble, France. ⟨hal-01950664⟩
  • Mariia Vladimirova, Julyan Arbel, Pablo Mesejo. Bayesian neural network priors at the level of units. Bayesian Statistics in the Big Data Era, Nov 2018, Marseille, France. pp.1. ⟨hal-01950660⟩
  • Caroline Lawless, Julyan Arbel. Chinese restaurant process from stick-breaking for Pitman-Yor. Bayesian learning theory for complex data modelling Workshop, Sep 2018, Grenoble, France. pp.1. ⟨hal-01950662⟩
  • Julyan Arbel, Jean-Bernard Salomond. Sequential Quasi Monte Carlo for Dirichlet Process Mixture Models. BNP 2017 - 11th Conference on Bayesian NonParametrics, Jun 2017, Paris, France. pp.1. ⟨hal-01667781⟩
  • Didier Fraix-Burnet, Charles Bouveyron, Stéphane Girard, Julyan Arbel. Unsupervised classification in high dimension. European Week of Astronomy and Space Science (EWASS 2017), Jun 2017, Prague, Czech Republic. 2017. ⟨hal-01569733⟩

Book sections5 documents

  • Kerrie K. Mengersen, Earl Duncan, Julyan Arbel, Clair Alston-Knox, Nicole White. Applications in Industry. Sylvia Fruhwirth-Schnatter; Gilles Celeux; Christian P. Robert. Handbook of mixture analysis, CRC press, pp.1-21, 2019, 9781498763813. ⟨hal-01963798⟩
  • Julyan Arbel. Clustering Milky Way's Globulars: a Bayesian Nonparametric Approach. Statistics for Astrophysics: Bayesian Methodology, pp.113-137, 2018. ⟨hal-01950656⟩
  • Julyan Arbel, Igor Prünster. Truncation error of a superposed gamma process in a decreasing order representation. Argiento, R.; Lanzarone, E.; Antoniano Villalobos, I.; Mattei, A. Bayesian Statistics in Action, 194, pp.11--19, 2017, Bayesian Statistics in Action. ⟨hal-01405580⟩
  • Guillaume Kon Kam King, Julyan Arbel, Igor Prünster. A Bayesian nonparametric approach to ecological risk assessment. Argiento, R.; Lanzarone, E.; Antoniano Villalobos, I.; Mattei, A. Bayesian Statistics in Action, 194, pp.151--159, 2017, Bayesian Statistics in Action. ⟨hal-01405593⟩
  • Julyan Arbel, Antonio Lijoi, Bernardo Nipoti. Bayesian Survival Model based on Moment Characterization. Sylvia Frühwirth-Schnatter, Angela Bitto, Gregor Kastner, Alexandra Posekany. Bayesian Statistics from Methods to Models and Applications, 126, pp.3-14, 2015, Springer Proceedings in Mathematics & Statistics, 978-3-319-16238-6. ⟨10.1007/978-3-319-16238-6_1⟩. ⟨hal-01203321⟩

Directions of work or proceedings1 document

  • Didier Fraix-Burnet, Stéphane Girard, Julyan Arbel, Jean-Baptiste Marquette. Statistics for Astrophysics: Bayesian Methodology. School of Stattistics for Astrophysics 2017: Bayesian Methodology, Oct 2017, Autrans, France. EDP Sciences, 2018, EDP Sciences Proceedings. ⟨hal-02132985⟩

Other publications1 document

  • Didier Fraix-Burnet, Stéphane Girard, Julyan Arbel, Jean-Baptiste Marquette. Statistics for Astrophysics: Bayesian Methodology. 2018. ⟨hal-01952759⟩

Preprints, Working Papers, ...7 documents

  • Théo Moins, Julyan Arbel, Anne Dutfoy, Stéphane Girard. On the use of a local $\hat R$ to improve MCMC convergence diagnostic. 2022. ⟨hal-03600407⟩
  • Julyan Arbel, Stéphane Girard, Hien Duy Nguyen, Antoine Usseglio-Carleve. Multivariate expectile-based distribution: properties, Bayesian inference, and applications. 2021. ⟨hal-03428827⟩
  • Daria Bystrova, Giovanni Poggiato, Julyan Arbel, Wilfried Thuiller. Latent factor models: a tool for dimension reduction in joint species distribution models. 2021. ⟨hal-03149452⟩
  • Daria Bystrova, Julyan Arbel, Thibaud Rahier. Contributed comment on Article by Hahn, Murray, and Carvalho. 2021. ⟨hal-03149459⟩
  • Florence Forbes, Hien Duy Nguyen, Trung Tin Nguyen, Julyan Arbel. Approximate Bayesian computation with surrogate posteriors. 2021. ⟨hal-03139256v4⟩
  • Julyan Arbel, Riccardo Corradin, Michal Lewandowski. Comment on Article by Wade and Ghahramani. 2018. ⟨hal-01950655⟩
  • Mariia Vladimirova, Julyan Arbel, Pablo Mesejo. Bayesian neural networks increasingly sparsify their units with depth. 2018. ⟨hal-01950657⟩

Theses1 document

Habilitation à diriger des recherches1 document

  • Julyan Arbel. Bayesian Statistical Learning and Applications. Methodology [stat.ME]. Université grenoble Alpes, CNRS, Institut des Géosciences et de l'Environnement, 2019. ⟨tel-02429156⟩