Zobrazeno 1 - 10
of 2 206
pro vyhledávání: '"Pereira Francisco A"'
Autor:
Costa, Miguel, Petersen, Morten W., Vandervoort, Arthur, Drews, Martin, Morrissey, Karyn, Pereira, Francisco C.
Due to climate change the frequency and intensity of extreme rainfall events, which contribute to urban flooding, are expected to increase in many places. These floods can damage transport infrastructure and disrupt mobility, highlighting the need fo
Externí odkaz:
http://arxiv.org/abs/2409.18574
Optogenetics is widely used to study the effects of neural circuit manipulation on behavior. However, the paucity of causal inference methodological work on this topic has resulted in analysis conventions that discard information, and constrain the s
Externí odkaz:
http://arxiv.org/abs/2405.18597
The development and use of large-scale quantum computers relies on integrating quantum error-correcting (QEC) schemes into the quantum computing pipeline. A fundamental part of the QEC protocol is the decoding of the syndrome to identify a recovery o
Externí odkaz:
http://arxiv.org/abs/2405.03776
Autor:
Dafflon, Jessica, Moraczewski, Dustin, Earl, Eric, Nielson, Dylan M., Loewinger, Gabriel, McClure, Patrick, Thomas, Adam G., Pereira, Francisco
One of the central objectives of contemporary neuroimaging research is to create predictive models that can disentangle the connection between patterns of functional connectivity across the entire brain and various behavioral traits. Previous studies
Externí odkaz:
http://arxiv.org/abs/2405.00255
Autor:
Amado, João Romeiras, Pereira, Francisco, Pissarra, David, Signorello, Salvatore, Correia, Miguel, Ramos, Fernando M. V.
Malicious traffic detectors leveraging machine learning (ML), namely those incorporating deep learning techniques, exhibit impressive detection capabilities across multiple attacks. However, their effectiveness becomes compromised when deployed in ne
Externí odkaz:
http://arxiv.org/abs/2403.18788
We perform an extended numerical search for practical fermion-to-qubit encodings with error correcting properties. Ideally, encodings should strike a balance between a number of the seemingly incompatible attributes, such as having a high minimum dis
Externí odkaz:
http://arxiv.org/abs/2402.15386
Bayesian active learning is based on information theoretical approaches that focus on maximising the information that new observations provide to the model parameters. This is commonly done by maximising the Bayesian Active Learning by Disagreement (
Externí odkaz:
http://arxiv.org/abs/2402.11973
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Psychiatry research seeks to understand the manifestations of psychopathology in behavior, as measured in questionnaire data, by identifying a small number of latent factors that explain them. While factor analysis is the traditional tool for this pu
Externí odkaz:
http://arxiv.org/abs/2312.07762
It is desirable to have accurate uncertainty estimation from a single deterministic forward-pass model, as traditional methods for uncertainty quantification are computationally expensive. However, this is difficult because single forward-pass models
Externí odkaz:
http://arxiv.org/abs/2308.10650
Autor:
Riis, Christoffer, Antunes, Francisco N., Bolić, Tatjana, Gurtner, Gérald, Cook, Andrew, Azevedo, Carlos Lima, Pereira, Francisco Câmara
The use of Air traffic management (ATM) simulators for planing and operations can be challenging due to their modelling complexity. This paper presents XALM (eXplainable Active Learning Metamodel), a three-step framework integrating active learning a
Externí odkaz:
http://arxiv.org/abs/2308.03404