Results 11 to 20 of about 8,736,022 (255)
A Review of Causality for Learning Algorithms in Medical Image Analysis
, 2022 Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area.
Vlontzos, Athanasios +2 more
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December 2021 course edition : Statistics and Machine Learning for Life Sciences
, 2021 course material for the SIB course - Statistics and Machine Learning for Life ...
Sébastien Boyer, Wandrille Duchemin
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Greedy structure learning from data that contain systematic missing values [PDF]
, 2022 Learning from data that contain missing values represents a common phenomenon in many domains. Relatively few Bayesian Network structure learning algorithms account for missing data, and those that do tend to rely on standard approaches that assume ...
Liu, Y +5 more
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Learning labelled dependencies in machine translation evaluation [PDF]
, 2009 Recently novel MT evaluation metrics have been presented which go beyond pure string matching, and which correlate better than other existing metrics with human judgements.
He, Yifan, Way, Andy
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Gaussian Processes for Machine Learning [PDF]
, 2005 A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.
Rasmussen, Carl Edward +1 more
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Generalized Energy-Based Models
, 2021 Presented online via Bluejeans Events on October 13, 2021 at 12:00 p.m.Arthur Gretton is a Professor with the Gatsby Computational Neuroscience Unit, and director of the Centre for Computational Statistics and Machine Learning (CSML) at UCL.
Gretton, Arthur
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
Towards a Theory of Representation Learning for Reinforcement Learning
, 2021 Presented online via Bluejeans Events on September 15, 2021 at 12:15 p.m.Alekh Agarwal is a researcher who works on theoretical foundations of machine learning, spanning many areas including large-scale and distributed optimization, high-dimensional ...
Agarwal, Alekh
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