Pablo Moreno-Muñoz
Research Fellow
Artificial Intelligence Group
Dept. of Information and Communication Technologies (DTIC)
Universitat Pompeu Fabra (UPF), Barcelona
pablo.moreno@upf.edu
Home | CV | GitHub | Google Scholar | Twitter
Peer-reviewed conferences and workshops
- N. Krämer, P. Moreno-Muñoz, H. Roy and S. Hauberg.
Gradients of Functions of Large Matrices,
In Advances in Neural Information Processing Systems (NeurIPS), 2024 (spotlight)
[preprint] [code] - S. Syrota, P. Moreno-Muñoz and S. Hauberg.
Decoder ensembling for learned latent geometries,
In Workshop on Geometry-grounded Representation Learning and Generative
Modeling (GRaM) @ ICML, 2024
[pdf] [code] - P. Moreno-Muñoz, P. G. Recasens and S. Hauberg.
On Masked Pre-training and the Marginal Likelihood,
In Advances in Neural Information Processing Systems (NeurIPS), 2023
[preprint] - F. Bergamin, P. Moreno-Muñoz, S. Hauberg and G. Arvanitidis.
Riemannian Laplace approximations for Bayesian neural networks,
In Advances in Neural Information Processing Systems (NeurIPS), 2023
[preprint] - P. G. Recasens, J. Torres. J. L. Bernal, S. Hauberg and P. Moreno-Muñoz.
Beyond Parameter Averaging in Model Aggregation,
In Workshop on Federated Learning in the Age of Foundation Models @ NeurIPS, 2023
[pdf] - S. Bartels, K. Stensbo-Smidt, P. Moreno-Muñoz, J. Frellsen, W. Boomsma and S. Hauberg.
Adaptive Cholesky Gaussian Processes,
In Artificial Intelligence and Statistics (AISTATS), 2023
[pdf] [preprint] [code] - M. Miani, F. Warburg, P. Moreno-Muñoz, N. S. Detlefsen and S. Hauberg.
Laplacian Autoencoders for Learning Stochastic Representations,
In Advances in Neural Information Processing Systems (NeurIPS), 2022
[pdf] [preprint] [code] - P. Moreno-Muñoz, C. W. Feldager and S. Hauberg.
Revisiting Active Sets for Gaussian Process Decoders,
In Advances in Neural Information Processing Systems (NeurIPS), 2022
[pdf] [preprint] [code] [poster] - P. Moreno-Muñoz, A. Artés-Rodríguez and M. A. Álvarez.
Modular Gaussian Processes for Transfer Learning,
In Advances in Neural Information Processing Systems (NeurIPS), 2021
[pdf] [preprint] [video] [poster] [slides] - P. Moreno-Muñoz, L. Romero-Medrano, A. Moreno, J. Herrera-López, E. Baca-García and A. Artés.
Passive Detection of Behavioral Shifts for Suicide Attempt Prevention,
In Machine Learning for Mobile Health Workshop @ NeurIPS, 2020
[pdf] - L. Romero-Medrano, P. Moreno-Muñoz and A. Artés-Rodríguez.
Multinomial Sampling for Hierarchical Change-point Detection,
In IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2020
[preprint] - P. Moreno-Muñoz, D. Ramírez and A. Artés-Rodríguez.
Continual Learning for Infinite Hierarchical Change-point Detection,
In International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
[preprint] [code] [video] - P. Moreno-Muñoz, A. Artés-Rodríguez and M. A. Álvarez.
Heterogeneous Multi-output Gaussian Process Prediction,
In Advances in Neural Information Processing Systems (NeurIPS), 2018 (spotlight)
[paper] [code] [video] [poster]
Preprints and ongoing works
- H. Roy, M. Miani, S. Syrota, J. Ye, E. Zainchkovskyy, S. Brack, F. Warburg,
N. Krämer, P. Moreno-Muñoz and S. Hauberg.
All Layers Marginal Likelihood Training with Fully Correlated Linearized
Laplace Approximations,
In preparation (soon in arXiv), 2023 - P. Moreno-Muñoz, P. Schwöbel and S. Hauberg.
Stochastic Combinatorics for Gaussian Processes,
In preparation, 2022 - H. Hauschultz, R. B. Palm, P. Moreno-Muñoz, N. S. Detlefsen, A. A. du Plessis and S. Hauberg.
Is an Encoder within Reach?,
In arXiv:2206.01552, 2022
[preprint] - P. Moreno-Muñoz, A. Artés-Rodríguez and M. A. Álvarez.
Continual Multi-task Gaussian Processes,
In arXiv:1911.00002, 2019, (work in progress)
[preprint] [code] [video]
Journals
- M. L. Barrigón, L. Romero-Medrano, P. Moreno-Muñoz, A. Porras-Segovia,
J. López-Castroman, A. Artés-Rodríguez and E. Baca-García.
One-week suicide risk prediction using real-time smartphone monitoring,
In Journal of Medical Internet Research (JMIR), 2023
[pdf] - L. Romero-Medrano, P. Moreno-Muñoz and A. Artés-Rodríguez.
Multinomial Sampling of Latent Variables for Hierarchical Change-point Detection,
In Journal of Signal Processing Systems - MLSP 2020 Special Issue, 2021
[paper] (extended version of workshop paper [pdf] ) - P. Moreno-Muñoz, D. Ramírez and A. Artés-Rodríguez.
Change-point Detection in Hierarchical Circadian Models,
In Pattern Recognition, 2020
[paper] [preprint] [code] - S. Berrouiguet, D. Ramírez, M. L. Barrigón, P. Moreno-Muñoz, R. Carmona, E. Baca-García and A. Artés-Rodríguez.
Combining continuous smartphone native sensors data capture and unsupervised data mining techniques for behavioral changes detection: A case series of the Evidence Based Behavior (eB2) study,
In Journal of Medical Internet Research (JMIR), 2018
[paper]
Dissertations
- P. Moreno-Muñoz.
Probabilistic Models for Human Behavior Learning
PhD Thesis, March 2021
[pdf] - P. Moreno-Muñoz.
Change Point Detection in Behavioral High Dimensional Data
Master Thesis (2/2), 2016 - P. Moreno-Muñoz.
Anomalous Behavior Detection in Psychiatry
Master Thesis (1/2), 2016 - P. Moreno-Muñoz.
Photometric Redshifts within crowded galaxy cluster fields
ESA Project Report, 2015 - P. Moreno-Muñoz.
Statistical learning costs with partial labels (spanish)
Bachelor Thesis, 2014