Deep Learning Building on Prior Ischemic Core Segmentation Improves Prediction of Infarction After Stroke
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Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...
London2024
Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...
Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...
New York2023
Owing to the diminishing returns of deep learning and the focus on model accuracy, machine learning for chemistry might become an endeavour exclusive to well-funded institutions and industry. Extending the focus to model efficiency and interpretability wil ...
NATURE PORTFOLIO2023
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This letter, addressed to a creature taking the form of a human chimera gathering the thoughts and knowledge of people who inspire and accompany us, recounts the experiences, affects and issues related to our first semester of teaching the course named DRA ...
Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...
Elsevier Science Inc2024
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Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. Methods A total of 542 patients with clini ...
This doctoral thesis focuses on a particular aspect of architectural learning as embodied cognition by studying, from a multidisciplinary approach, the creative processes and design actions that accompany the conception and construction of space. Due to th ...
USP- Universidad San Pablo CEU, Madrid, Spain.2023
Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...
EPFL2023
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Motivated by alternating game-play in two-player games, we study an altenating variant of the Online Linear Optimization (OLO). In alternating OLO, a learner at each round t ∈[n] selects a vector xt and then an adversary selects a cost-vector ct ∈[−1,1]n. ...