Výsledky vyhledávání - "Vinas, Ramon"

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gRNAde: Geometric Deep Learning for 3D RNA inverse design

Autor: Joshi, Chaitanya K., Jamasb, Arian R., Viñas, Ramon, Harris, Charles, Mathis, Simon V., Morehead, Alex, Anand, Rishabh, Liò, Pietro

Computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity. We introduce gRNAde, a geometric RNA

Externí odkaz: http://arxiv.org/abs/2305.14749

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A Graph-based Imputation Method for Sparse Medical Records

Autor: Vinas, Ramon, Zheng, Xu, Hayes, Jer

Electronic Medical Records (EHR) are extremely sparse. Only a small proportion of events (symptoms, diagnoses, and treatments) are observed in the lifetime of an individual. The high degree of missingness of EHR can be attributed to a large number of

Externí odkaz: http://arxiv.org/abs/2111.09084

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Attentional Meta-learners for Few-shot Polythetic Classification

Autor: Day, Ben, Viñas, Ramon, Simidjievski, Nikola, Liò, Pietro

Polythetic classifications, based on shared patterns of features that need neither be universal nor constant among members of a class, are common in the natural world and greatly outnumber monothetic classifications over a set of features. We show th

Externí odkaz: http://arxiv.org/abs/2106.05317

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Investigating Estimated Kolmogorov Complexity as a Means of Regularization for Link Prediction

Autor: Flood, Paris D. L., Viñas, Ramon, Liò, Pietro

Link prediction in graphs is an important task in the fields of network science and machine learning. We investigate a flexible means of regularization for link prediction based on an approximation of the Kolmogorov complexity of graphs that is diffe

Externí odkaz: http://arxiv.org/abs/2006.04258

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