Physics-enhanced machine learning with symmetry-adapted and long-range representations
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In this paper, a mixed numerical-experimental identification procedure for characterising the storage and loss properties in sandwich structures with a relatively stiff core is developed. At the computational level, the proposed method is based upon an ori ...
In this work, we present a magnetic measurement system for integration into smart knee prostheses to accurately measure the combination of two knee rotations; namely Flexion- Extension and Internal-External rotations. This measurement system consists of tw ...
Institute of Electrical and Electronics Engineers2013
Recovering the 3D deformations of a non-rigid surface from a single viewpoint has applications in many domains such as sports, entertainment, and medical imaging. Unfortunately, without any knowledge of the possible deformations that the object of interest ...
We present a method for retrieving illuminant spectra from a set of images taken with a fixed location camera, such as a surveillance or panoramic one. In these images, there will be significant changes in lighting conditions and scene content, but there w ...
White matter hyperintensities (WMH) are the focus of intensive research and have been linked to cognitive impairment and depression in the elderly. Cumbersome manual outlining procedures make research on WMH labour intensive and prone to subjective bias. T ...
We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists in iteratively improving an appearance based model built with a Boosting pro ...
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011
We present a probabilistic viewpoint to multiple kernel learning unifying well-known regularised risk approaches and recent advances in approximate Bayesian inference relaxations. The framework proposes a general objective function suitable for regression, ...
Computational neuroscience is a branch of the neurosciences that attempts to elucidate the principles underlying the operation of neurons with the help of mathematical modeling. In contrast with a number of fields pursuing a tightly related goal, such as m ...
Speaker Diarization is the process of partitioning an audio input into homogeneous segments according to speaker identity where the number of speakers in a given audio input is not known a priori. This master thesis presents a novel initialization method f ...
Controlled doping of SrCu2(BO3)(2), a faithful realization of the Heisenberg spin-1/2 antiferromagnet on the Shastry-Sutherland lattice, with nonmagnetic impurities generates bound states below the spin gap. These bound states and their symmetry properties ...