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Marco Fraccaro
Marco Fraccaro
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Sequential neural models with stochastic layers
M Fraccaro, SK Sønderby, U Paquet, O Winther
Advances in neural information processing systems, 2199-2207, 2016
3222016
A disentangled recognition and nonlinear dynamics model for unsupervised learning
M Fraccaro, S Kamronn, U Paquet, O Winther
Advances in Neural Information Processing Systems, 3601-3610, 2017
2292017
BIVA: A very deep hierarchy of latent variables for generative modeling
L Maaløe, M Fraccaro, V Liévin, O Winther
Advances in neural information processing systems, 6548-6558, 2019
1232019
Machine learning meets mathematical optimization to predict the optimal production of offshore wind parks
M Fischetti, M Fraccaro
Computers & Operations Research 106, 289-297, 2019
362019
A deep learning approach to adherence detection for type 2 diabetics
A Mohebbi, TB Aradottir, AR Johansen, H Bengtsson, M Fraccaro, ...
2017 39th Annual International Conference of the IEEE Engineering in …, 2017
342017
Semi-supervised generation with cluster-aware generative models
L Maaløe, M Fraccaro, O Winther
arXiv preprint arXiv:1704.00637, 2017
322017
Generative temporal models with spatial memory for partially observed environments
M Fraccaro, D Rezende, Y Zwols, A Pritzel, SMA Eslami, F Viola
International Conference on Machine Learning, 1549-1558, 2018
252018
Indexable probabilistic matrix factorization for maximum inner product search
M Fraccaro, U Paquet, O Winther
Thirtieth AAAI Conference on Artificial Intelligence, 2016
192016
Palm area detection for reliable hand gesture recognition
G Marin, M Fraccaro, M Donadeo, F Dominio, P Zanuttigh
Proceedings of MMSP 2013, 120, 2013
192013
Deep latent variable models for sequential data
M Fraccaro
PhD thesis, Technical University of Denmark, 2018
102018
Using OR+ AI to predict the optimal production of offshore wind parks: a preliminary study
M Fischetti, M Fraccaro
International Conference on Optimization and Decision Science, 203-211, 2017
92017
Perturbation theory for variational inference
M Opper, M Fraccaro, U Paquet, A Susemihl, O Winther
NIPS WS, 2015
52015
An efficient implementation of Riemannian manifold Hamiltonian Monte Carlo for Gaussian process models
U Paquet, M Fraccaro
arXiv preprint arXiv:1810.11893, 2018
42018
CaGeM: A cluster aware deep generative model
L Maaløe, M Fraccaro, O Winther
NIPS Workshop on Advances in Approximate Bayesian Inference, Long Beach, CA …, 2017
32017
An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants
M Fraccaro, U Paquet, O Winther
arXiv preprint arXiv:1604.01972, 2016
32016
The added effect of artificial intelligence on physicians’ performance in detecting thoracic pathologies on CT and chest X-ray: A systematic review
D Li, LM Pehrson, CA Lauridsen, L Tøttrup, M Fraccaro, D Elliott, ...
Diagnostics 11 (12), 2206, 2021
12021
Learning to index
M Fraccaro
Technical University of Denmark, 2014
2014
Learning to index
M Fraccaro
Technical University of Denmark, 2014
2014
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling Download PDF
L Maaløe, M Fraccaro, V Liévin, O Winther
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