Publications

Highlighted papers

• 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. [pdf, 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]

• 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. [pdf, code, video] (spotlight)

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. [preprint, code] (spotlight)

• 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]

• 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, code]

• P. G. Recasens, J. Torres. J. L. Bernal, S. Hauberg and P. Moreno-Muñoz. Beyond Parameter Averaging in Model Aggregation. In Artificial Intelligence and Statistics (AISTATS), 2023. [preprint]

• 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, A. Artés-Rodríguez and M. A. Álvarez. Modular Gaussian Processes for Transfer Learning. In Advances in Neural Information Processing Systems (NeurIPS), 2021. [pdf, preprint, code, video]

• P. Moreno-Muñoz, L. Romero-Medrano, A. Moreno, J. Herrera-López, E. Baca-García and A. Artés-Rodríguez. 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) [pdf]

• 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. [pdf, code, video]

Preprints and ongoing works

• 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. [pdf]

• P. Moreno-Muñoz, A. Artés-Rodríguez and M. A. Álvarez. Continual Multi-task Gaussian Processes. In arXiv:1911.00002, 2019. [preprint, code, video]

Journal articles

• 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). [pdf]

• L. Romero-Medrano, P. Moreno-Muñoz and A. Artés-Rodríguez. Multinomial Sampling of Latent Variables for Hierarchical Change-point Detection. In Pattern Recognition, 2020. [pdf, preprint]

• 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. [pdf]

Dissertations

• P. Moreno-Muñoz. Probabilistic Models for Human Behavior Learning, PhD Thesis, Universidad Carlos III de Madrid, 2021. [pdf]

• P. Moreno-Muñoz. Change Point Detection in Behavioral High Dimensional Data. MSc Thesis, Universidad Carlos III de Madrid (2/2), 2016.

• P. Moreno-Muñoz. Anomalous Behavior Detection in Psychiatry. MSc Thesis, Universidad Carlos III de Madrid (1/2), 2016.

• P. Moreno-Muñoz. Photometric Redshifts within crowded galaxy cluster fieldsy. ESA-ESAC Project Report, 2015.

• P. Moreno-Muñoz. Statistical learning costs with partial labels. BSc Thesis, Universidad Carlos III de Madrid, 2014. (in spanish)