Our paper on "Hellinger loss function for Generative Adversarial Networks" is posted in arXiv at http://arxiv.org/abs/2512.12267
#Statistics
#HellingerDistance
#NeuralNetworks
#GenerativeAdversarialNetworks
#RobustStatistics
#InfluenceFunction
Professor of Statistics, Department of Mathematics, University of Trento, Italy.
Our paper on "Hellinger loss function for Generative Adversarial Networks" is posted in arXiv at http://arxiv.org/abs/2512.12267
#Statistics
#HellingerDistance
#NeuralNetworks
#GenerativeAdversarialNetworks
#RobustStatistics
#InfluenceFunction
Abstract submission and registration is open for DSSV 2026 (Trento). See https://datascience.maths.unitn.it/dssv2026/ for full information.
#DSSV2026
#daTascieNce
#StatsUnitn
#stats
#Statistics
#DataVisulization
#Conference
#Trento
05-06 February 2026 short course by Angela Andreella on Multiple Testing and Beyond: From Error Control to Post-hoc Inference. Full information at https://datascience.maths.unitn.it/events/mt2026/index.html
#daTascieNce
#StatsUnitn
#MultipleTesting
02 February 2026 seminar by Laura D'angelo on A Bayesian nonparametric approach to discriminant analysis. Full information at https://datascience.maths.unitn.it/events/bnp2026/index.html
#daTascieNce
#StatsUnitn
#BayesianNonParametric
#DiscriminantAnalysis
Our paper on "Central subspace data depth" is posted in arXiv at https://arxiv.org/abs/2601.14947
#StatisticalDataDepth
#CentralSubspace
#Symmetry
#Statistics
#DimensionReduction
#ProjectionPursuit
Our paper on "Temporally-Evolving Generalised Networks and Their Kernels" is accepted in Statistica Sinica, see it at https://www3.stat.sinica.edu.tw/ss_newpaper/SS-2024-0345_na.pdf
or in arXiv at https://arxiv.org/abs/2309.15855
#MetricGraphs
#EuclideanGraphs
#Networks
#StochasticProcesses
#Kernels
#CovarianceMatrices
#EvolvingNetworks
#SpatialProcesses
Our paper on "Robust penalized estimators for high-dimensional
generalized linear models" is accepted in TEST, see it at https://link.springer.com/article/10.1007/s11749-025-00978-6
or in arXiv at https://arxiv.org/abs/2312.04661
#HighDimension
#GeneralizedLinearModels
#PenalizedMethods
#RobustStatistics
#MT-Estimators
Our paper on "A Regularized MANOVA Test for Semicontinuous High-Dimensional Data" is accepted in Biometrical Journal, see it at https://doi.org/10.1002/bimj.70054
#HighDimension
#StatisticalTest
#PermutationTest
#SemicontinuousData
#RidgePenalization
29-30 May 2025 short course by Geir Storvik on Statistical aspects to epidemiological models. Full information at
https://datascience.maths.unitn.it/events/saem2025/index.html
#daTascieNce
#StatsUnitn
#Epidemiology
26-28 May 2025 short course by Sabrina Giordano on Hidden Markov Models for Categorical Data: Methods and Practice with R. Full information at
https://datascience.maths.unitn.it/events/hmm2025/index.html
#datTascieNce
#StatsUnitn
#HiddenMarkvoModels
Our paper on "Torus Probabilistic Principal Component Analysis" is now accepted in Journal of Classification, see the arXiv version at
https://arxiv.org/abs/2008.10725
#TorusData
#PPCA
21 March 2025 seminar by Ruggero Bellio on Consistent and Scalable Composite Likelihood Estimation of Probit Models with Crossed Random Effects. Full information at
https://datascience.maths.unitn.it/events/cl2025/index.html
#daTascieNce
#StatsUnitn
#CompositeLikelihood
Registration is open for the summer school "Robust Statistics: Theory and Computation" to be held in Ispra (Varese), on 15-17 May 2025.
Information at
https://datascience.maths.unitn.it/icors2025/school.html
#RobustStatistics
#SummerSchool
Registration and submission of abstract are open for the International Conference on Robust Statistics 2025 (ICORS2025).
All the information at
https://datascience.maths.unitn.it/icors2025
#RobustStatistics
#ICORS2025
Our joint work "Vector-Valued Gaussian Processes and their Kernels on a Class of Metric Graphs" by Tobia Filosi, Emilio Porcu, Xavier Emery, Claudio Agostinelli, Alfredo Alegrìa is now available on arXiv
https://arxiv.org/abs/2501.10208
14 February 2025 seminar by Peter Filzmoser on Outlier identification and explanation for matrix-valued observations. Full information at https://datascience.maths.unitn.it/events/oi2025/index.html
#RobustStatistics
#daTascieNce