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2024
Bonet D, Mas-Montserrat D, Giró-i-Nieto X, Ioannidis AG. HyperFast: Instant Classification for Tabular Data. In 38th Annual AAAI Conference on Artificial Intelligence (AAAI). 2024.  (3.15 MB)
Schürholt K. Hyper-Representations: Learning from Populations of Neural Networks. Mahoney M, Giró-i-Nieto X, Borth D. University of St. Gallen. 2024.  (18.12 MB)
Calm B, Cumplido-Mayoral I, Gispert JDomingo, Vilaplana V. Identifying brain ageing trajectories using variational autoencoders with regression model in neuroimaging data stratified by sex and validated against dementia-related risk factors. In 7th International Workshop on PRedictive Intelligence in MEdicine, MICCAI 2024. 2024.
Hernandez C. Implementation of personalized medicine in malignant melanoma patients aided by artificial intelligence. Vilaplana V. Signal Theory and Communications. 2024.
Hernandez C, Pachón-García C, Delicado P, Vilaplana V. Interpreting Machine Learning Models for Survival Analysis: A Study of Cutaneous Melanoma Using the SEER Database. In Explainable Artificial Intelligence and Process Mining Applications for Healthcare,. Springer, Cham; 2024.
Seguí A, Ugalde A, Ventosa S, Morros JR. Lossless and Lossy Compression for Distributed Acoustic Sensing Using Inter-channel Predictions. In SSA Photonic Seismology 2024. Vancouver; 2024.
Cumplido-Mayoral I, Brugulat-Serra A, Sánchez-Benavides G, Molinuevo JLuis, Suarez-Calvet M, Vilaplana V, et al.. The mediating role of neuroimaging-derived biological brain age between risk factors for dementia and cognitive decline in middle/late-aged asymptomatic individuals: a cohort study. The Lancet Healthy Longevity. 2024;.
Pachón-García C, Hernandez C, Delicado P, Vilaplana V. SurvLIMEpy: A Python package implementing SurvLIME. Expert Systems With Applications. 2024;237, Part C.
Giardina C, Vilaplana V, Pardàs M, Guardia O. Synthesis of Prostate MRI Scans: A Comparison of StyleGAN2-ADA and Latent Diffusion Models. In Conferencia de la Asociación Española para la Inteligencia Artificial, IABioMed workshop. 2024.
Theodoropoulou E, Lyberopoulos G, Setaki F, García-Gómez P, Royo S, Marcus C, et al.. Towards AI-Enhanced Fibre-Wireless Optical 6G Network in Support of Connected Mobility. In Athens: IEEE; 2024.  (1.13 MB)
Pina O, Vilaplana V. Unsupervised Domain Adaptation for Multi-Stain Cell Detection in Breast Cancer with Transformers. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (DEF-AI-MIA workshop). 2024.
2023
Barrabés M, Mas-Montserrat D, Geleta M, Giró-i-Nieto X, Ioannidis AG. Adversarial Learning for Feature Shift Detection and Correction. In Neural Information Processing Systems (NeurIPS). New Orleans, USA; 2023.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex. eLife. 2023;12.
Cumplido-Mayoral I, Brugulat-Serrat A, Sánchez-Benavides G, González-Escalante A, Anastasi F, Mila-Aloma M, et al.. Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum. In Alzheimer’s Association International Conference (AAIC). Amsterdam, Netherlands; 2023.
Cumplido-Mayoral I, Mila-Aloma M, Falcon C, Cacciaglia R, Minguillon C, Fauria K, et al.. Brain-age prediction and its associations with glial and synaptic CSF markers. In Alzheimer's Association International Conference. Amsterdam, Netherlands; 2023.
Casamitjana A, Sala-Llonch R, Tudela R, Andrés A, Orío S, Casas J, et al.. Deep Learning CT segmentation for dosimetry in postoperative endometrial carcinoma treatment. In XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica. Cartagena: Ediciones UPCT. Universidad Politécnica de Cartagena; 2023.
Baldrich A, Paugam R, Casas J, Pardàs M, Àgueda A, Parsons R, et al.. Deep learning-based methodology for smoke plume segmentation of wildfire images. In 14th International Symposium on Fire Safety Science (IAFSS2023). Tsukuba, Japan: International Association for Fire Safety Science (IAFSS); 2023.  (146.88 KB)
Geleta M, Mas-Montserrat D, Giró-i-Nieto X, Ioannidis AG. Deep Variational Autoencoders for Population Genetics. 2023;.
de-Mas-Giménez G, García-Gómez P, Casas J, Royo S. Gradient-Based Metrics for the Evaluation of Image Defogging. World Electric Vehicle Journal. 2023;14(9).  (4.92 MB)
Mosella-Montoro A. Graph Convolutional Neural Networks for 3D Data Analysis. Ruiz-Hidalgo J. Signal Theory and Communications. [Barcelona]: Universitat Politècnica de Catalunya; 2023.
Hernandez C, Pachón-García C, Delicado P, Vilaplana V. Interpreting Machine Learning models for Survival Analysis: A study of Cutaneous Melanoma using the SEER Database. In XAI-Healthcare 2023 Workshop at 21st International Conference of Artificial Intelligence in Medicine (AIME 2023). Portoroz, Slovenia; 2023.
Fernàndez D. Knowledge graph population from news streams. Marqués F, Giró-i-Nieto X, Bou-Balust E. Signal Theory and Communications. [Barcelona, Catalonia]: Universitat Politècnica de Catalunya; 2023.  (6.07 MB)
Pina O, Vilaplana V. Layer-wise self-supervised learning on graphs. In KDD 2023 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD 2023). Long Beach, USA; 2023.
Gené-Mola J, Ferrer-Ferrer M, Gregorio E, Blok PM, Hemming J, Morros JR, et al.. Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation. Computers and Electronics in Agriculture. 2023;209.  (9.02 MB)
Dominguez A, Mas-Montserrat D, Bustamante C, Giró-i-Nieto X, Ioannidis AG. Neural ADMIXTURE: rapid population clustering with autoencoders. Nature Computational Science. 2023;.

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