Enabling Personalized Decision Support with Patient-Generated Data and Attributable Components. (arXiv:1911.09856v1 [stat.AP])

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Decision-making related to health is complex. Machine learning (ML) and patient generated data can identify patterns and insights at the individual level, where human cognition falls short, but not all ML-generated information is of equal utility for making health-related decisions. We develop and apply attributable components analysis (ACA), a method inspired by optimal transport theory,…

Data Programming using Continuous and Quality-Guided Labeling Functions. (arXiv:1911.09860v1 [cs.LG])

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Scarcity of labeled data is a bottleneck for supervised learning models. A paradigm that has evolved for dealing with this problem is data programming. An existing data programming paradigm allows human supervision to be provided as a set of discrete labeling functions (LF) that output possibly noisy labels to input instances and a generative modelfor…

Subjective Logic-based Identification of Markov Chains and Its Application to CAV’s Safety. (arXiv:1911.09950v1 [eess.SP])

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A reliable estimation of the communication chan-nel which connects automated vehicles is an important steptowards the safety of connected and automated vehicles. The communication channel is usually modeled as Markov chain with slowly time-varying transition rates and is identifiedthrough statistics on the observed state transitions. However, the classical identification approach lacks a measure on how…

SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation. (arXiv:1911.09968v1 [cs.CV])

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In the last decade, numerous supervised deep learning approaches requiring large amounts of labeled data have been proposed for visual-inertial odometry (VIO) and depth map estimation. To overcome the data limitation, self-supervised learning has emerged as a promising alternative, exploiting constraints such as geometric and photometric consistency in the scene. In this study, we introduce…

6-O-glucose palmitate synthesis with lipase: Investigation of some key parameters. (arXiv:1911.09920v1 [q-bio.BM])

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Fatty acid sugar esters represent an important class of non-ionic bio-based surfactants. They can be synthesized from vinyl fatty acids and sugars with enzyme as a catalyst. Herein, the influence of the solvent, the lipase and the temperature on a model reaction between vinyl palmitate and glucose via enzymatic catalysis has been investigated and the…

Decision Making guided by Emotion A computational architecture. (arXiv:1911.09948v1 [q-bio.NC])

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A computational architecture is presented, in which “swift and fuzzy” emotional channels guide a “slow and precise” decision-making channel. Reported neurobiological studies first provide hints on the representation of both emotional and cognitive dimensions across brain structures, mediated by the neuromodulation system. The related model is based on Guided Propagation Networks, the inner flows of…

Alignment of Protein-Protein Interaction Networks. (arXiv:1911.09959v1 [q-bio.QM])

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PPI network alignment aims to find topological and functional similarities between networks of different species. Several alignment approaches have been proposed. Each of these approaches relies on a different alignment method and uses different biological information during the alignment process such as the topological structure of the networks and the sequence similarities between the proteins,…

Artificial neural networks in action for an automated cell-type classification of biological neural networks. (arXiv:1911.09977v1 [cs.NE])

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In this work we address the problem of neuronal cell-type classification, and we employ a real-world dataset of raw neuronal activity measurements obtained with calcium imaging techniques. While neuronal cell-type classification is a crucial step in understanding the function of neuronal circuits, and thus a systematic classification of neurons is much needed, it still remains…