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learning, focusing on identifying abrupt shifts in the properties of data over time. These shifts, commonly referred to as change-points, indicate transitions in the underlying distribution or dynamics of a
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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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. Processing this response provides estimates of the local variations in acoustic pressure along the fiber, over distances ranging from 40km up to 140km with some systems. This technique, called Distributed
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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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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We are looking for a candidate with a Master's degree, Engineer's degree or PhD in computer science, junior or senior, to join a team responsible for the packaging, deployment, and testing