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Angelopoulos, Stephen Bates, et al. Conformal prediction: A gentle introduction. Foundations and Trends® in Machine Learning, 16(4):494–591, 2023. Arthur P Dempster, Nan M Laird, and Donald B Rubin. Maximum
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
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The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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toxicities. The proposed thesis aims to extract biomarkers that are predictive of the response to targeted therapy for patients with KRAS-mutant non-small cell lung cancer. To this end, machine learning
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statistics and machine learning, focused on identifying abrupt shifts in the properties of data over time. These shifts, known as change-points, indicate transitions in the underlying distribution or dynamics
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secure energy transmission and electrical power quality. Addressing these fields requires a forward-looking vision where digital technologies and dependable grids are integrated. The application of machine
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of the scientific publications • Motivation letter • Letter of recommendation of the thesis supervisor Description of the topic: Change-point detection (CPD) is a fundamental problem in statistics and machine
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frontier of cardiac electrophysiology” as it continues to puzzle cardiologists [JAN14]. Physiological signal analysis and machine learning arise a key tools to improve the understanding and management