Ramón Viñas

According to our database, Ramón Viñas authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease.

Elisa Gómez de Lope, Saurabh Deshpande, Ramón Viñas Torné, Pietro Liò, Enrico Glaab, Stéphane P. A. Bordas

CoRR, 2024

2023

Hypergraph factorization for multi-tissue gene expression imputation.

Ramón Viñas, Chaitanya K. Joshi, Dobrik Georgiev, Phillip Lin, Bianca Dumitrascu, Eric R. Gamazon, Pietro Liò

Nat. Mac. Intell., July, 2023

Hypergraph Factorisation Expression Quantitative Trait Loci.

Ramón Viñas, Chaitanya K. Joshi, Dobrik Georgiev, Phillip Lin, Bianca Dumitrascu, Pietro Liò, Eric R. Gamazon

Dataset, May, 2023

Multi-State RNA Design with Geometric Multi-Graph Neural Networks.

Chaitanya K. Joshi, Arian R. Jamasb, Ramón Viñas, Charles Harris, Simon V. Mathis, Pietro Liò

CoRR, 2023

2022

Classification of datasets with imputed missing values: does imputation quality matter?

Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb

CoRR, 2022

Adversarial generation of gene expression data.

Ramón Viñas, Helena Andrés-Terré, Pietro Liò, Kevin Bryson

Bioinform., 2022

Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases.

Paul Scherer, Maja Trebacz, Nikola Simidjievski, Ramón Viñas, Zohreh Shams, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò

Bioinform., 2022

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.

Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Attentional Meta-learners for Few-shot Polythetic Classification.

Ben J. Day, Ramón Viñas Torné, Nikola Simidjievski, Pietro Lió

Proceedings of the International Conference on Machine Learning, 2022

2021

A Graph-based Imputation Method for Sparse Medical Records.

Ramón Viñas, Xu Zheng, Jer Hayes

CoRR, 2021

An investigation of pre-upsampling generative modelling and Generative Adversarial Networks in audio super resolution.

James King, Ramón Viñas Torné, Alexander Campbell, Pietro Liò

CoRR, 2021

Graph Representation Learning on Tissue-Specific Multi-Omics.

Amine Amor, Pietro Lio', Vikash Singh, Ramón Viñas Torné, Helena Andrés-Terré

CoRR, 2021

Attentional meta-learners are polythetic classifiers.

Ben Day, Ramón Viñas, Nikola Simidjievski, Pietro Liò

CoRR, 2021

2020

pietrobarbiero/digital-patient: Absolutno.

Pietro Barbiero, Ramón Viñas Torné, Pietro Liò

Dataset, September, 2020

Graph representation forecasting of patient's medical conditions: towards a digital twin.

Pietro Barbiero, Ramón Viñas Torné, Pietro Lió

CoRR, 2020

Kolmogorov Regularization for Link Prediction.

Paris D. L. Flood, Ramón Viñas, Pietro Liò

CoRR, 2020