Ponències/Comunicacions de congressos
Recent Submissions
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Model-free reinforcement learning with a non-linear reconstructor for closed-loop adaptive optics control with a pyramid wavefront sensor
(International Society for Photo-Optical Instrumentation Engineers (SPIE), 2022)
Conference report
Open AccessWe present a model-free reinforcement learning (RL) predictive model with a supervised learning non-linear reconstructor for adaptive optics (AO) control with a pyramid wavefront sensor (P-WFS). First, we analyse the ... -
Single-view 3d body and cloth reconstruction under complex poses
(Scitepress, 2022)
Conference report
Open AccessRecent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense ... -
Molecular dynamics forecasting of transmembrane regions in GPRCs by recurrent neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessG protein-coupled receptors are a large super-family of cell membrane proteins that play an important physiological role as transmitters of extra-cellular signals. Signal transmission through the cell membrane depends on ... -
A deep learning-based method for uncovering GPCR ligand-induced conformational states using interpretability techniques
(Springer, 2022)
Conference report
Restricted access - publisher's policyThere is increasing interest in the development of tools for investigating the protein ligand space. Understanding the underlying mechanisms of G protein-coupled receptors (GPCR) in the ligand-binding process is of particular ... -
Measuring alignment bias in neural Seq2Seq semantic parsers
(Association for Computational Linguistics, 2022)
Conference report
Open AccessPrior to deep learning the semantic parsing community has been interested in understanding and modeling the range of possible word alignments between natural language sentences and their corresponding meaning representations. ... -
Testing reinforcement learning explainability methods in a multi-agent cooperative environment
(IOS Press, 2022)
Conference report
Open AccessThe adoption of algorithms based on Artificial Intelligence (AI) has been rapidly increasing during the last years. However, some aspects of AI techniques are under heavy scrutiny. For instance, in many cases, it is not ... -
Focus and bias: will it blend?
(IOS Press, 2022)
Conference report
Open AccessOne direct application of explainable AI feature attribution methods is to be used for detecting unwanted biases. To do so, domain experts typically have to review explained inputs, checking for the presence of unwanted ... -
Bootstrap-CURE clustering: An investigation of impact of shrinking on clustering performance
(IOS Press, 2022)
Conference report
Open AccessHierarchical clustering is one of the most popular techniques in unsupervised segmentation. However, since it has quadratic complexity as it is based on pairwise distance matrix construction, it tends to be less used with ... -
Optimizing online time-series data imputation through case-based reasoning
(IOS Press, 2022)
Conference report
Open AccessWhen working with Intelligent Decision Support Systems (IDSS), data quality could compromise decisions and therefore, an undesirable behaviour of the supported system. In this paper, a novel methodology for time-series ... -
Long short-term memory to predict 3D amino acids positions in GPCR molecular dynamics
(IOS Press, 2022)
Conference report
Open AccessG-Protein Coupled Receptors (GPCRs) are a big family of eukaryotic cell transmembrane proteins, responsible for numerous biological processes. From a practical viewpoint around 34% of the drugs approved by the US Food and ... -
Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference lecture
Open AccessIncreasing a ML model accuracy is not enough, we must also increase its trustworthiness. This is an important step for building resilient AI systems for safety-critical applications such as automotive, finance, and healthcare. ... -
Obstruction level detection of sewers videos using convolutional neural networks
(International journal of structural and civil engineering research (IJSCER), 2021)
Conference report
Open AccessWorldwide, sewer networks are designed to transport wastewater to a centralized treatment plant to be treated and returned to the environment. This is a critical process for preventing waterborne illnesses, providing safe ...
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