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Connecting Hospitals and Health Centres Could Benefit Most of Porto's Children Population - Current Trends in Paedriatic Patients' Mobility between Institutions Requires Implementation of Electronic Patient Records.

A. Edral, A. Matos, B. Soares, C. Leite, J. Almeida, J. Girão, J. Nunes, M. Pereira, M. Lobato, M. Silva, R. Boaventura, S. Faria, and R. Correia. HEALTHINF (2), page 305-310. INSTICC - Institute for Systems and Technologies of Information, Control and Communication, (2008)978-989-8111-16-6.

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Lisette Lobato Mendonca

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Other publications of authors with the same name

Connecting Hospitals and Health Centres Could Benefit Most of Porto's Children Population - Current Trends in Paedriatic Patients' Mobility between Institutions Requires Implementation of Electronic Patient Records.A. Edral, A. Matos, B. Soares, C. Leite, J. Almeida, J. Girão, J. Nunes, M. Pereira, M. Lobato, M. Silva and 3 other author(s). HEALTHINF (2), page 305-310. INSTICC - Institute for Systems and Technologies of Information, Control and Communication, (2008)978-989-8111-16-6.Actively Learning what makes a Discrete Sequence Valid.D. Janz, J. van der Westhuizen, and J. Hernández-Lobato. CoRR, (2017)Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters.M. Havasi, R. Peharz, and J. Hernández-Lobato. CoRR, (2018)Gaussianity Measures for Detecting the Direction of Causal Time Series.J. Hernández-Lobato, P. Morales-Mombiela, and A. Suárez. IJCAI, page 1318-1323. IJCAI/AAAI, (2011)Cold-start Active Learning with Robust Ordinal Matrix Factorization.N. Houlsby, J. Hernández-Lobato, and Z. Ghahramani. ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 766-774. JMLR.org, (2014)Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.J. Hernández-Lobato, N. Houlsby, and Z. Ghahramani. ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 379-387. JMLR.org, (2014)Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space.J. Hernández-Lobato, J. Requeima, E. Pyzer-Knapp, and A. Aspuru-Guzik. ICML, volume 70 of Proceedings of Machine Learning Research, page 1470-1479. PMLR, (2017)'In-Between' Uncertainty in Bayesian Neural NetworksA. Foong, Y. Li, J. Hernández-Lobato, and R. Turner. (2019)cite arxiv:1906.11537Comment: Presented at the ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning.Flow Annealed Importance Sampling Bootstrap.L. Midgley, V. Stimper, G. Simm, B. Schölkopf, and J. Hernández-Lobato. CoRR, (2022)Fast and Painless Image Reconstruction in Deep Image Prior Subspaces.R. Barbano, J. Antorán, J. Leuschner, J. Hernández-Lobato, Z. Kereta, and B. Jin. CoRR, (2023)