Data driven approximation of parametrized PDEs by reduced basis and neural networks

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Measuring perceptual similarity is a key tool in computer vision. In recent years perceptual metrics based on features extracted from neural networks with large and diverse training sets, e.g. CLIP, have become popular. At the same time, the metrics extrac ...

One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of ima ...

Accurately and rapidly simulating the hysteretic behavior of double skin composite wall (DSCW) under earthquake loads enhance the efficiency of seismic performance assessments for high-rise steel-concrete composite structures. The application of artificial ...

Solving optimization problems is a key task for which quantum computers could possibly provide a speedup over the best known classical algorithms. Particular classes of optimization problems including semidefinite programming (SDP) and linear programming ( ...

Deep learning models have shown great promise in estimating tissue microstructure from limited diffusion magnetic resonance imaging data. However, these models face domain shift challenges when test and train data are from different scanners and protocols, ...

Spherical harmonics provide a smooth, orthogonal, and symmetry-adapted basis to expand functions on a sphere, and they are used routinely in physical and theoretical chemistry as well as in different fields of science and technology, from geology and atmos ...

We use numerical bootstrap techniques to study correlation functions of traceless sym-metric tensors of O(N) with two indices ti j. We obtain upper bounds on operator dimen-sions for all the relevant representations and several values of N. We discover sev ...

Nanocrystal (NC)-sensitized triplet-fusion upconversion is a rising strategy to convert long-wavelength, incoherent light into higher-energy output photons. Here, we chart the photophysics of tailor-functionalized CdSe NCs to understand energy transfer to ...

Within the reduced basis methods approach, an effective low-dimensional subspace of a quantum many-body Hilbert space is constructed in order to investigate, e.g., the ground-state phase diagram. The basis of this subspace is built from solutions of snapsh ...

The increasing integration of Machine Learning (ML) techniques into clinical care, driven in particular by Deep Learning (DL) using Artificial Neural Nets (ANNs), promises to reshape medical practice on various levels and across multiple medical fields. Mu ...

Nature fabricates hard functional materials from soft organic scaffolds that are mineralized. To enable an energy-efficient locomotion of these creatures while maintaining their structural stability, nature often renders parts of these minerals porous. Unf ...

We theoretically and experimentally investigate the formation of dissipative coherent structures in Kerr nonlinear optical microresonators, whose spectrum encompasses an integrated dispersion that exceeds the cavity free-spectral range. We are able to acce ...

Background After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiol ...

Layered hybrid perovskites are based on organic spacers separating hybrid perovskite slabs. We employ arene and perfluoroarene moieties based on 1,4-phenylenedimethylammonium (PDMA) and its perfluorinated analogue (F-PDMA) in the assembly of hybrid layered ...

Terahertz and far-infrared techniques are combined with complementary Raman and inelastic neutron scattering results to probe the low-energy phonon dynamics of archetypal antiferroelectric candidate - francisite (Cu3Bi(SeO3)(2)O2Cl). The combined results c ...

Deep learning (DL) has shown remarkable results in solving inverse problems in various domains. In particular, the Tikhonet approach is very powerful in deconvolving optical astronomical images. However, this approach only uses the l(2) loss, which does no ...

Relying on the previously developed charge-based approaches, this paper presents a physics-based design space of negative capacitance in double-gate and bulk MOSFET architectures. The impact of thickness variation of the ferroelectric on the DC characteris ...

The recent discovery of topologically nontrivial behavior in Co3Sn2S2 stimulated a notable interest in this itinerant ferromagnet (T-C = 174 K). The exact magnetic state remains ambiguous, with several reports indicating the existence of a second transitio ...

The Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings. Abstraction entails identifying the essential visual properties of an object or scene, which requires semantic understanding and prior knowledge of high-lev ...

Data driven approximation of parametrized PDEs by reduced basis and neural networks

Chattez avec Graph Search

Adversarially Robust CLIP Models Can Induce Better (Robust) Perceptual Metrics

Meteorological information prediction using images from webcams

Machine learning-aided hysteretic response prediction of double skin composite wall under earthquake loads

Slack-variable Approach for Variational Quantum Semidefinite Programming

Cross-Age and Cross-Site Domain Shift Impacts on Deep Learning-Based White Matter Fiber Estimation in Newborn and Baby Brains

Fast evaluation of spherical harmonics with sphericart

Bootstrapping traceless symmetric O(N) scalars

Sequential Carrier Transfer Can Accelerate Triplet Energy Transfer from Functionalized CdSe Nanocrystals

Reduced basis surrogates for quantum spin systems based on tensor networks

Machine learning and its impact on psychiatric nosology: Findings from a qualitative study among German and Swiss experts

Additive Manufacturing of Porous Biominerals

Dissipative Solitons and Switching Waves in Dispersion-Modulated Kerr Cavities

what If...? Pandemic Policy-decision-support to Guide a Cost-benefit-optimised, Country- Specific Response

Nanosegregation in arene-perfluoroarene pi-systems for hybrid layered Dion-Jacobson perovskites

Soft-mode dynamics and sublattice polarization in an archetypal antiferroelectric

ShapeNet: Shape constraint for galaxy image deconvolution

Design Space of Negative Capacitance in FETs

Unraveling the origin of the peculiar transition in the magnetically ordered phase of theWeyl semimetal Co3Sn2S2

MPEG-G Reference-Based Compression of Unaligned Reads Through Ultra-Fast Alignments

CLIPasso: Semantically-Aware Object Sketching