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Diffusion models (DMs) have emerged as powerful tools for modeling complex data distributions and generating realistic new samples. Over the years, advanced architectures and sampling methods have been developed to make these models…

Machine Learning · Computer Science 2025-12-11 Roi Benita , Michael Elad , Joseph Keshet

In disordered materials under mechanical stress, the produced deformation can deviate from the affine one already in the elastic regime. The nonaffine contribution was observed and characterized in numerical simulations for various systems.…

Soft Condensed Matter · Physics 2021-12-17 Alesya Mikhailovskaya , Julien Fade , Jérôme Crassous

The network management community has explored and exploited light, copper, and several wireless spectra (including acoustics) as a medium to transfer control or data traffic. Meanwhile, haptic technologies are being explored in end-user…

Networking and Internet Architecture · Computer Science 2020-03-24 John Pasquesi , Flavio Esposito , Gianluca Davoli , Jenna Gorlewicz

We discuss the numerically stable, spectral-domain computation and extraction of the scattered electromagnetic field excited by distributed sources embedded in planar-layered environments, where each layer may exhibit arbitrary and…

Computational Physics · Physics 2016-02-17 Kamalesh Sainath , Fernando L. Teixeira

We investigate the flow of granular material in a rotating cylinder numerically using molecular dynamics in two dimensions. The particles are described by a new model which allows to simulate geometrically complicated shaped grains. The…

Materials Science · Physics 2015-06-24 Volkhard Buchholtz , Thorsten Poeschel , Hans-Juergen Tillemans

Nonlinear spectroscopy provides a unique perspective to understand time-resolved molecular dynamics under vibrational strong coupling (VSC). Herein, equilibrium-nonequilibrium cavity molecular dynamics simulations are performed to compute…

Chemical Physics · Physics 2026-03-26 Xinwei Ji , Tomislav Begusic , Tao E. Li

In most cases the ultrafast dynamics of resonantly excited molecules are considered, and almost always computed in the molecular frame, while experiments are carried out in the laboratory frame. Here we provide a formalism in terms of a lab…

Chemical Physics · Physics 2022-11-09 Margaret Gregory , Simon Neville , Michael Schuurman , Varun Makhija

Understanding the spectral properties of kernels offers a principled perspective on generalization and representation quality. While deep models achieve state-of-the-art accuracy in molecular property prediction, kernel methods remain…

Machine Learning · Computer Science 2025-10-17 Asma Jamali , Tin Sum Cheng , Rodrigo A. Vargas-Hernández

The topological nature of the disorder of glasses and supercooled liquids strongly affects their high-frequency dynamics. In order to understand its main features, we analytically studied a simple topologically disordered model, where the…

Disordered Systems and Neural Networks · Physics 2009-11-07 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Verrocchio

This work is devoted to the stability/resolution analysis of several imaging functionals in complex environments. We consider both linear functionals in the wavefield as well as quadratic functionals based on wavefield correlations. Using…

Analysis of PDEs · Mathematics 2015-01-27 G. Bal , O. Pinaud , L. Ryzhik

Many protein design applications, such as binder or enzyme design, require scaffolding a structural motif with high precision. Generative modelling paradigms based on denoising diffusion processes emerged as a leading candidate to address…

Machine Learning · Computer Science 2024-03-15 Kieran Didi , Francisco Vargas , Simon V Mathis , Vincent Dutordoir , Emile Mathieu , Urszula J Komorowska , Pietro Lio

We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples. This problem arises in scientific applications where access to uncorrupted samples is impossible or expensive to…

Machine Learning · Computer Science 2023-05-31 Giannis Daras , Kulin Shah , Yuval Dagan , Aravind Gollakota , Alexandros G. Dimakis , Adam Klivans

Porous carbonaceous materials have many important industrial applications including energy storage, water purification, and adsorption of volatile organic compounds. Most of their applications rely upon the adsorption of molecules or ions…

Materials Science · Physics 2020-12-15 Alexander C. Forse , Céline Merlet , Clare P. Grey , John M. Griffin

The structure of amorphous silicon (a-Si) has been studied for decades. The two main theories are based on a continuous random network and on a `paracrystalline' model, respectively -- the latter being defined as showing localized…

Materials Science · Physics 2024-07-24 Louise A. M. Rosset , David A. Drabold , Volker L. Deringer

Quantifying the relationship between geometric descriptors of microstructure and effective properties like permeability is essential for understanding and improving the behavior of porous materials. In this paper, we employ a previously…

Materials Science · Physics 2023-11-27 Matthias Weber , Andreas Grießer , Dennis Mosbach , Erik Glatt , Andreas Wiegmann , Volker Schmidt

Boron nitride (BN) is a structurally versatile insulator since it can be found in several crystalline structures with interesting mechanical and electrical properties, making this material attractive for technological applications. Seeking…

Structurally and chemically complex materials such as amorphous metallosilicates underpin major catalytic and separation technologies, yet their intrinsic complexity challenges reliable atomistic modeling under realistic conditions.…

Pathologies associated with calcified tissue, such as osteoporosis, demand in vivo and/or in situ spectroscopic analysis to assess the role of chemical substitutions in the inorganic component. High energy X-ray or NMR spectroscopies are…

While analyzing mobile systems we often approximate the actual coverage surface and assume an ideal cell shape. In a multi-cellular network, because of its tessellating nature, a hexagon is more preferred than a circular geometry. Despite…

Information Theory · Computer Science 2013-06-04 Mouhamed Abdulla , Yousef R. Shayan

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala