ERAF: A R Package for Regression and Forecasting. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (WIRN, 2004)

Unsupervised Gene Selection and Clustering Using Simulated Annealing. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (WILF, 2005)

Soft Rank Clustering. - Stefano Rovetta; Francesco Masulli; Maurizio Filippone (WIRN/NAIS, 2005)

Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta; Sushmita Mitra; Haider Banka (CMSB, 2006)

Supervised Classification and Gene Selection Using Simulated Annealing. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (IJCNN, 2006)

Local Learning of Tide Level Time Series using a Fuzzy Approach. - Elio Canestrelli; P. Canestrelli; Marco Corazza; Maurizio Filippone; Silvio Giove; Francesco Masulli (IJCNN, 2007)

SVM-Based Time Series Prediction with Nonlinear Dynamics Methods. - Francesco Camastra; Maurizio Filippone (KES (3), 2007)

Membership Embedding Space Approach and Spectral Clustering. - Stefano Rovetta; Francesco Masulli; Maurizio Filippone (KES (3), 2007)

Possibilistic Clustering in Feature Space. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (WILF, 2007)

Stability and Performances in Biclustering Algorithms. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (CIBB, 2008)

Detecting Suspicious Behavior in Surveillance Images. - Daniel Barbará; Carlotta Domeniconi; Zoran Duric; Maurizio Filippone; Richard Mansfield; Edgard Lawson (ICDM Workshops, 2008)

An Experimental Comparison of Kernel Clustering Methods. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (WIRN, 2008)

A survey of kernel and spectral methods for clustering. - Maurizio Filippone; Francesco Camastra; Francesco Masulli; Stefano Rovetta (Pattern Recognit., 2008)

The discriminating power of random features. - Stefano Rovetta; Francesco Masulli; Maurizio Filippone (WIRN, 2009)

Dealing with non-metric dissimilarities in fuzzy central clustering algorithms. - Maurizio Filippone (Int. J. Approx. Reason., 2009)

Clustering in the membership embedding space. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (Int. J. Knowl. Eng. Soft Data Paradigms, 2009)

Soft ranking in clustering. - Stefano Rovetta; Francesco Masulli; Maurizio Filippone (Neurocomputing, 2009)

A comparative evaluation of nonlinear dynamics methods for time series prediction. - Francesco Camastra; Maurizio Filippone (Neural Comput. Appl., 2009)

Information theoretic novelty detection. - Maurizio Filippone; Guido Sanguinetti (Pattern Recognit., 2010)

Applying the Possibilistic c-Means Algorithm in Kernel-Induced Spaces. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (IEEE Trans. Fuzzy Syst., 2010)

Approximate inference of the bandwidth in multivariate kernel density estimation. - Maurizio Filippone; Guido Sanguinetti (Comput. Stat. Data Anal., 2011)

Discussion of the paper: "Sampling schemes for generalized linear Dirichlet process random effects models" by M. Kyung, J. Gill, and G. Casella. - Maurizio Filippone; Antonietta Mira; Mark A. Girolami (Stat. Methods Appl., 2011)

Simulated annealing for supervised gene selection. - Maurizio Filippone; Francesco Masulli; Stefano Rovetta (Soft Comput., 2011)

A Perturbative Approach to Novelty Detection in Autoregressive Models. - Maurizio Filippone; Guido Sanguinetti (IEEE Trans. Signal Process., 2011)

Predicting the conflict level in television political debates: an approach based on crowdsourcing, nonverbal communication and gaussian processes. - Samuel Kim; Maurizio Filippone; Fabio Valente; Alessandro Vinciarelli (ACM Multimedia, 2012)

From speech to personality: mapping voice quality and intonation into personality differences. - Gelareh Mohammadi; Antonio Origlia; Maurizio Filippone; Alessandro Vinciarelli (ACM Multimedia, 2012)

Towards Causal Modeling of Human Behavior. - Matteo Campo; Anna Polychroniou; Hugues Salamin; Maurizio Filippone; Alessandro Vinciarelli (WIRN, 2012)

ODE parameter inference using adaptive gradient matching with Gaussian processes. - Frank Dondelinger; Dirk Husmeier; Simon Rogers; Maurizio Filippone (AISTATS, 2013)

Exact-Approximate Bayesian Inference for Gaussian Processes. - Maurizio Filippone; Mark A. Girolami (CoRR, 2013)

A comparative evaluation of stochastic-based inference methods for Gaussian process models. - Maurizio Filippone; Mingjun Zhong; Mark A. Girolami (Mach. Learn., 2013)

Aggregation Algorithm Towards Large-Scale Boolean Network Analysis. - Yin Zhao; Jongrae Kim; Maurizio Filippone (IEEE Trans. Autom. Control., 2013)

Editorial A Successful Change From TNN to TNNLS and a Very Successful Year. - Derong Liu 001; Charles Anderson 001; Ahmad Taher Azar; Giorgio Battistelli; Eduardo Bayro-Corrochano; Cristiano Cervellera; David A. Elizondo; Maurizio Filippone; Giorgio Gnecco; Xiaolin Hu; Tingwen Huang; Weifeng Liu 001; et al. (IEEE Trans. Neural Networks Learn. Syst., 2013)

Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC. - Maurizio Filippone (ICPR, 2014)

Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data. - Andrew D. O'Harney; Andre F. Marquand; Katya Rubia; Kaylita Chantiluke; Anna B. Smith; Ana Cubillo; Camilla Blain; Maurizio Filippone (ICPR, 2014)

Pseudo-Marginal Bayesian Inference for Gaussian Processes. - Maurizio Filippone; Mark A. Girolami (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Predicting Continuous Conflict Perceptionwith Bayesian Gaussian Processes. - Samuel Kim; Fabio Valente; Maurizio Filippone; Alessandro Vinciarelli (IEEE Trans. Affect. Comput., 2014)

Monte Carlo Strength Evaluation: Fast and Reliable Password Checking. - Matteo Dell'Amico; Maurizio Filippone (CCS, 2015)

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE). - Maurizio Filippone; Raphael Engler (ICML, 2015)

MCMC for Variationally Sparse Gaussian Processes. - James Hensman; Alexander G. de G. Matthews; Maurizio Filippone; Zoubin Ghahramani (NIPS, 2015)

On User Availability Prediction and Network Applications. - Matteo Dell'Amico; Maurizio Filippone; Pietro Michiardi; Yves Roudier (IEEE/ACM Trans. Netw., 2015)

Parameter Inference in Differential Equation Models of Biopathways Using Time Warped Gradient Matching. - Mu Niu; Simon Rogers; Maurizio Filippone; Dirk Husmeier (CIBB, 2016)

Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation Using Statistical Emulation. - Umberto Noè; Weiwei Chen; Maurizio Filippone; Nicholas Hill; Dirk Husmeier (CIBB, 2016)

Preconditioning Kernel Matrices. - Kurt Cutajar; Michael A. Osborne; John P. Cunningham; Maurizio Filippone (ICML, 2016)

Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching. - Mu Niu; Simon Rogers; Maurizio Filippone; Dirk Husmeier (ICML, 2016)

Looking Good With Flickr Faves: Gaussian Processes for Finding Difference Makers in Personality Impressions. - Xiaoyu Xiong; Maurizio Filippone; Alessandro Vinciarelli (ACM Multimedia, 2016)

Mini-Batch Spectral Clustering. - Yufei Han 001; Yun Shen; Maurizio Filippone (CoRR, 2016)

Random Feature Expansions for Deep Gaussian Processes. - Kurt Cutajar; Edwin V. Bonilla; Pietro Michiardi; Maurizio Filippone (ICML, 2017)

Mini-batch spectral clustering. - Yufei Han; Maurizio Filippone (IJCNN, 2017)

Entropic Trace Estimates for Log Determinants. - Jack K. Fitzsimons; Diego Granziol; Kurt Cutajar; Michael A. Osborne; Maurizio Filippone; Stephen J. Roberts (ECML/PKDD (1), 2017)

Bayesian Inference of Log Determinants. - Jack K. Fitzsimons; Kurt Cutajar; Maurizio Filippone; Michael A. Osborne; Stephen J. Roberts (UAI, 2017)

AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models. - Karl Krauth; Edwin V. Bonilla; Kurt Cutajar; Maurizio Filippone (UAI, 2017)

Decentralized Deep Scheduling for Interference Channels. - Paul de Kerret; David Gesbert; Maurizio Filippone (CoRR, 2017)

Team Deep Neural Networks for Interference Channels. - Paul de Kerret; David Gesbert; Maurizio Filippone (ICC Workshops, 2018)

Constraining the Dynamics of Deep Probabilistic Models. - Marco Lorenzi; Maurizio Filippone (ICML, 2018)

Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification. - Dimitrios Milios; Raffaello Camoriano; Pietro Michiardi; Lorenzo Rosasco; Maurizio Filippone (NeurIPS, 2018)

Variational Calibration of Computer Models. - Sébastien Marmin; Maurizio Filippone (CoRR, 2018)

Statistical inference in mechanistic models: time warping for improved gradient matching. - Mu Niu; Benn Macdonald; Simon Rogers; Maurizio Filippone; Dirk Husmeier (Comput. Stat., 2018)

Deep Gaussian Process autoencoders for novelty detection. - Remi Domingues; Pietro Michiardi; Jihane Zouaoui; Maurizio Filippone (Mach. Learn., 2018)

A comparative evaluation of outlier detection algorithms: Experiments and analyses. - Remi Domingues; Maurizio Filippone; Pietro Michiardi; Jihane Zouaoui (Pattern Recognit., 2018)

Calibrating Deep Convolutional Gaussian Processes. - Gia-Lac Tran; Edwin V. Bonilla; John P. Cunningham; Pietro Michiardi; Maurizio Filippone (AISTATS, 2019)

Good Initializations of Variational Bayes for Deep Models. - Simone Rossi 001; Pietro Michiardi; Maurizio Filippone (ICML, 2019)

Pseudo-Extended Markov chain Monte Carlo. - Christopher Nemeth; Fredrik Lindsten; Maurizio Filippone; James Hensman (NeurIPS, 2019)

Exact gaussian process regression with distributed computations. - Duc-Trung Nguyen; Maurizio Filippone; Pietro Michiardi (SAC, 2019)

Sparsification as a Remedy for Staleness in Distributed Asynchronous SGD. - Rosa Candela; Giulio Franzese; Maurizio Filippone; Pietro Michiardi (CoRR, 2019)

Efficient Approximate Inference with Walsh-Hadamard Variational Inference. - Simone Rossi 001; Sébastien Marmin; Maurizio Filippone (CoRR, 2019)

Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease. - Marco Lorenzi; Maurizio Filippone; Giovanni B. Frisoni; Daniel C. Alexander; Sébastien Ourselin (NeuroImage, 2019)

LIBRE: Learning Interpretable Boolean Rule Ensembles. - Graziano Mita; Paolo Papotti; Maurizio Filippone; Pietro Michiardi (AISTATS, 2020)

Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units. - Ruben Ohana; Jonas Wacker; Jonathan Dong; Sébastien Marmin; Florent Krzakala; Maurizio Filippone; Laurent Daudet (ICASSP, 2020)

Walsh-Hadamard Variational Inference for Bayesian Deep Learning. - Simone Rossi 001; Sébastien Marmin; Maurizio Filippone (NeurIPS, 2020)

Model Monitoring and Dynamic Model Selection in Travel Time-Series Forecasting. - Rosa Candela; Pietro Michiardi; Maurizio Filippone; Maria A. Zuluaga (ECML/PKDD (4), 2020)

A comparative evaluation of novelty detection algorithms for discrete sequences. - Rémi Domingues; Pietro Michiardi; Jérémie Barlet; Maurizio Filippone (Artif. Intell. Rev., 2020)

Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations. - Simone Rossi 001; Markus Heinonen; Edwin V. Bonilla; Zheyang Shen; Maurizio Filippone (CoRR, 2020)

A Variational View on Bootstrap Ensembles as Bayesian Inference. - Dimitrios Milios; Pietro Michiardi; Maurizio Filippone (CoRR, 2020)

Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling. - Giulio Franzese; Rosa Candela; Dimitrios Milios; Maurizio Filippone; Pietro Michiardi (CoRR, 2020)

Learning Optimal Conditional Priors For Disentangled Representations. - Graziano Mita; Maurizio Filippone; Pietro Michiardi (CoRR, 2020)

Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations. - Simone Rossi 001; Markus Heinonen; Edwin V. Bonilla; Zheyang Shen; Maurizio Filippone (AISTATS, 2021)

Towards a generic deep learning pipeline for traffic measurements. - Raphaël Azorin; Massimo Gallo; Alessandro Finamore; Maurizio Filippone; Pietro Michiardi; Dario Rossi 001 (StudentWorkshop@CoNEXT, 2021)

An Identifiable Double VAE For Disentangled Representations. - Graziano Mita; Maurizio Filippone; Pietro Michiardi (ICML, 2021)

Sparse within Sparse Gaussian Processes using Neighbor Information. - Gia-Lac Tran; Dimitrios Milios; Pietro Michiardi; Maurizio Filippone (ICML, 2021)

Multimodal Variational Autoencoders for Sensor Fusion and Cross Generation. - Matthieu Da Silva-Filarder; Andrea Ancora; Maurizio Filippone; Pietro Michiardi (ICMLA, 2021)

Model Selection for Bayesian Autoencoders. - Ba-Hien Tran; Simone Rossi 001; Dimitrios Milios; Pietro Michiardi; Edwin V. Bonilla; Maurizio Filippone (NeurIPS, 2021)

A Unified View of Stochastic Hamiltonian Sampling. - Giulio Franzese; Dimitrios Milios; Maurizio Filippone; Pietro Michiardi (CoRR, 2021)

A Scalable Bayesian Sampling Method Based on Stochastic Gradient Descent Isotropization. - Giulio Franzese; Dimitrios Milios; Maurizio Filippone; Pietro Michiardi (Entropy, 2021)

Revisiting the Effects of Stochasticity for Hamiltonian Samplers. - Giulio Franzese; Dimitrios Milios; Maurizio Filippone; Pietro Michiardi (ICML, 2022)

Locally Smoothed Gaussian Process Regression. - Davit Gogolashvili; Bogdan L. Kozyrskiy; Maurizio Filippone (KES, 2022)

Variational Bootstrap for Classification. - Bogdan L. Kozyrskiy; Dimitrios Milios; Maurizio Filippone (KES, 2022)

Local Random Feature Approximations of the Gaussian Kernel. - Jonas Wacker; Maurizio Filippone (KES, 2022)

Complex-to-Real Random Features for Polynomial Kernels. - Jonas Wacker; Ruben Ohana; Maurizio Filippone (CoRR, 2022)

All You Need is a Good Functional Prior for Bayesian Deep Learning. - Ba-Hien Tran; Simone Rossi 001; Dimitrios Milios; Maurizio Filippone (J. Mach. Learn. Res., 2022)

Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel. - Jonas Wacker; Ruben Ohana; Maurizio Filippone (AISTATS, 2023)

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes. - Ba-Hien Tran; Babak Shahbaba; Stephan Mandt; Maurizio Filippone (ICML, 2023)

Imposing Functional Priors on Bayesian Neural Networks. - Bogdan L. Kozyrskiy; Dimitrios Milios; Maurizio Filippone (ICPRAM, 2023)

Continuous-Time Functional Diffusion Processes. - Giulio Franzese; Giulio Corallo; Simone Rossi 001; Markus Heinonen; Maurizio Filippone; Pietro Michiardi (NeurIPS, 2023)

One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models. - Ba-Hien Tran; Giulio Franzese; Pietro Michiardi; Maurizio Filippone (NeurIPS, 2023)

Continuous-Time Functional Diffusion Processes. - Giulio Franzese; Simone Rossi 001; Dario Rossi 001; Markus Heinonen; Maurizio Filippone; Pietro Michiardi (CoRR, 2023)

When is Importance Weighting Correction Needed for Covariate Shift Adaptation? - Davit Gogolashvili; Matteo Zecchin; Motonobu Kanagawa; Marios Kountouris; Maurizio Filippone (CoRR, 2023)

Multi-timestep models for Model-based Reinforcement Learning. - Abdelhakim Benechehab; Giuseppe Paolo; Albert Thomas 001; Maurizio Filippone; Balázs Kégl (CoRR, 2023)

Spatial Bayesian Neural Networks. - Andrew Zammit-Mangion; Michael D. Kaminski; Ba-Hien Tran; Maurizio Filippone; Noel Cressie (CoRR, 2023)

How Much Is Enough? A Study on Diffusion Times in Score-Based Generative Models. - Giulio Franzese; Simone Rossi 001; Lixuan Yang; Alessandro Finamore; Dario Rossi 001; Maurizio Filippone; Pietro Michiardi (Entropy, 2023)

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; et al. (ICML, 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; et al. (CoRR, 2024)

Variational DAG Estimation via State Augmentation With Stochastic Permutations. - Edwin V. Bonilla; Pantelis Elinas; He Zhao 001; Maurizio Filippone; Vassili Kitsios; Terry O'Kane (CoRR, 2024)

A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning. - Abdelhakim Benechehab; Albert Thomas 001; Giuseppe Paolo; Maurizio Filippone; Balázs Kégl (CoRR, 2024)

Improved Random Features for Dot Product Kernels. - Jonas Wacker; Motonobu Kanagawa; Maurizio Filippone (J. Mach. Learn. Res., 2024)

Robust Classification by Coupling Data Mollification with Label Smoothing. - Markus Heinonen; Ba-Hien Tran; Michael Kampffmeyer; Maurizio Filippone (AISTATS, 2025)

Unconditionally Calibrated Priors for Beta Mixture Density Networks. - Alix Lhéritier; Maurizio Filippone (AISTATS, 2025)

Zero-shot Model-based Reinforcement Learning using Large Language Models. - Abdelhakim Benechehab; Youssef Attia El Hili; Ambroise Odonnat; Oussama Zekri; Albert Thomas 001; Giuseppe Paolo; Maurizio Filippone; Ievgen Redko; Balázs Kégl (ICLR, 2025)

Gaussian Processes with Bayesian Inference of Covariate Couplings. - Mattia Rosso; Juho Ylä-Jääski; Zheyang Shen; Markus Heinonen; Maurizio Filippone (Trans. Mach. Learn. Res., 2025)

AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting. - Abdelhakim Benechehab; Vasilii Feofanov; Giuseppe Paolo; Albert Thomas 001; Maurizio Filippone; Balázs Kégl (CoRR, 2025)

Optimizing Data Augmentation through Bayesian Model Selection. - Madi Matymov; Ba-Hien Tran; Michael Kampffmeyer; Markus Heinonen; Maurizio Filippone (CoRR, 2025)

Variational Inference for Quantum HyperNetworks. - Luca Nepote; Alix Lhéritier; Nicolas Bondoux; Marios Kountouris; Maurizio Filippone (CoRR, 2025)

Scaling Laws for Uncertainty in Deep Learning. - Mattia Rosso; Simone Rossi 001; Giulio Franzese; Markus Heinonen; Maurizio Filippone (CoRR, 2025)

GANs Secretly Perform Approximate Bayesian Model Selection. - Maurizio Filippone; Marius P. Linhard (CoRR, 2025)