Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. - Marco Fraccaro; Ulrich Paquet; Ole Winther (AAAI, 2016)

Sequential Neural Models with Stochastic Layers. - Marco Fraccaro; Søren Kaae Sønderby; Ulrich Paquet; Ole Winther (NIPS, 2016)

A deep learning approach to adherence detection for type 2 diabetics. - Ali Mohebbi 001; Tinna B. Aradottir; Alexander Rosenberg Johansen; Henrik Bengtsson; Marco Fraccaro; Morten Mørup (EMBC, 2017)

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. - Marco Fraccaro; Simon Kamronn; Ulrich Paquet; Ole Winther (NIPS, 2017)

Semi-Supervised Generation with Cluster-aware Generative Models. - Lars Maaløe; Marco Fraccaro; Ole Winther (CoRR, 2017)

Generative Temporal Models with Spatial Memory for Partially Observed Environments. - Marco Fraccaro; Danilo Jimenez Rezende; Yori Zwols; Alexander Pritzel; S. M. Ali Eslami; Fabio Viola (ICML, 2018)

An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models. - Ulrich Paquet; Marco Fraccaro (CoRR, 2018)

Deep Latent Variable Models for Sequential Data. - Marco Fraccaro (2018)

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. - Lars Maaløe; Marco Fraccaro; Valentin Liévin; Ole Winther (NeurIPS, 2019)

Machine learning meets mathematical optimization to predict the optimal production of offshore wind parks. - Martina Fischetti; Marco Fraccaro (Comput. Oper. Res., 2019)

Towards Clinically Useful AI: From Radiology Practices in Global South and North to Visions of AI Support. - Hubert Dariusz Zajac; Tariq O. Andersen; Elijah Kwasa; Ruth Wanjohi; Mary K. Onyinkwa; Edward K. Mwaniki; Samuel N. Gitau; Shawnim S. Yaseen; Jonathan Frederik Carlsen; Marco Fraccaro; Michael Bachmann Nielsen; Yunan Chen (ACM Trans. Comput. Hum. Interact., 2025)