Marco Fraccaro

According to our database1, Marco Fraccaro authored at least 10 papers between 2016 and 2019.

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Bibliography

2019
Machine learning meets mathematical optimization to predict the optimal production of offshore wind parks.
Comput. Oper. Res., 2019

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Deep Latent Variable Models for Sequential Data.
PhD thesis, 2018

An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models.
CoRR, 2018

Generative Temporal Models with Spatial Memory for Partially Observed Environments.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Semi-Supervised Generation with Cluster-aware Generative Models.
CoRR, 2017

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A deep learning approach to adherence detection for type 2 diabetics.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2016
Sequential Neural Models with Stochastic Layers.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016


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