Filippone, Maurizio

38 publications

ICML 2025 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

ICLRW 2025 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

TMLR 2025 Gaussian Processes with Bayesian Inference of Covariate Couplings Mattia Rosso, Juho Ylä-Jääski, Zheyang Shen, Markus Heinonen, Maurizio Filippone

AISTATS 2025 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

ICLR 2025 Zero-Shot Model-Based Reinforcement Learning Using Large Language Models Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl

JMLR 2024 Improved Random Features for Dot Product Kernels Jonas Wacker, Motonobu Kanagawa, Maurizio Filippone

ICML 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 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

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

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

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

ICMLW 2023 Improving Training of Likelihood-Based Generative Models with Gaussian Homotopy Ba-Hien Tran, Giulio Franzese, Pietro Michiardi, Maurizio Filippone

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

JMLR 2022 All You Need Is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone

ICML 2022 Revisiting the Effects of Stochasticity for Hamiltonian Samplers Giulio Franzese, Dimitrios Milios, Maurizio Filippone, Pietro Michiardi

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

ICML 2021 An Identifiable Double VAE for Disentangled Representations Graziano Mita, Maurizio Filippone, Pietro Michiardi

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

ICML 2021 Sparse Within Sparse Gaussian Processes Using Neighbor Information Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone

AISTATS 2020 LIBRE: Learning Interpretable Boolean Rule Ensembles Graziano Mita, Paolo Papotti, Maurizio Filippone, Pietro Michiardi

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

NeurIPS 2020 Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi, Sebastien Marmin, Maurizio Filippone

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

ICML 2019 Good Initializations of Variational Bayes for Deep Models Simone Rossi, Pietro Michiardi, Maurizio Filippone

NeurIPS 2019 Pseudo-Extended Markov Chain Monte Carlo Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman

ICML 2018 Constraining the Dynamics of Deep Probabilistic Models Marco Lorenzi, Maurizio Filippone

MLJ 2018 Deep Gaussian Process Autoencoders for Novelty Detection Remi Domingues, Pietro Michiardi, Jihane Zouaoui, Maurizio Filippone

NeurIPS 2018 Dirichlet-Based Gaussian Processes for Large-Scale Calibrated Classification Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone

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

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

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

ICML 2017 Random Feature Expansions for Deep Gaussian Processes Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, 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 Preconditioning Kernel Matrices Kurt Cutajar, Michael Osborne, John Cunningham, Maurizio Filippone

ICML 2015 Enabling Scalable Stochastic Gradient-Based Inference for Gaussian Processes by Employing the Unbiased LInear System SolvEr (ULISSE) Maurizio Filippone, Raphael Engler

NeurIPS 2015 MCMC for Variationally Sparse Gaussian Processes James Hensman, Alexander G Matthews, Maurizio Filippone, Zoubin Ghahramani

MLJ 2013 A Comparative Evaluation of Stochastic-Based Inference Methods for Gaussian Process Models Maurizio Filippone, Mingjun Zhong, Mark A. Girolami

AISTATS 2013 ODE Parameter Inference Using Adaptive Gradient Matching with Gaussian Processes Frank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone