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Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex aqueous systems such as solid-liquid interfaces. Here, we present a machine learning…

Image clustering is one of the most important computer vision applications, which has been extensively studied in literature. However, current clustering methods mostly suffer from lack of efficiency and scalability when dealing with…

Machine Learning · Computer Science 2017-08-10 Kamran Ghasedi Dizaji , Amirhossein Herandi , Cheng Deng , Weidong Cai , Heng Huang

In this paper, we propose conjugate energy-based models (CEBMs), a new class of energy-based models that define a joint density over data and latent variables. The joint density of a CEBM decomposes into an intractable distribution over…

Machine Learning · Computer Science 2021-06-28 Hao Wu , Babak Esmaeili , Michael Wick , Jean-Baptiste Tristan , Jan-Willem van de Meent

Spectral clustering is a leading clustering method. Two of its major shortcomings are the disjoint optimization process and the limited representation capacity. To address these issues, we propose a deep spectral clustering model (named…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Wengang Guo , Wei Ye , Chunchun Chen , Xin Sun , Christian Böhm , Claudia Plant , Susanto Rahardja

We have investigated thermodynamic and dynamic properties as well as the dielectric constant of water-metha\-nol model mixtures in the entire range of composition by using constant pressure molecular dynamics simulations at ambient…

Soft Condensed Matter · Physics 2015-12-25 E. Galicia-Andrés , H. Dominguez , L. Pusztai , O. Pizio

High harmonic generation (HHG) takes place in all phases of matter. In gaseous atomic and molecular media, it has been extensively studied and is very well-understood. In solids research is ongoing, but a consensus is forming for the…

Chemical Physics · Physics 2022-06-22 Ofer Neufeld , Zahra Nourbakhsh , Nicolas Tancogne-Dejean , Angel Rubio

We analyze the nature of the structural order established in liquid TIP4P water in the framework provided by the multi-particle correlation expansion of the statistical entropy. Different regimes are mapped onto the phase diagram of the…

Materials Science · Physics 2011-10-25 Rubens Esposito , Franz Saija , A. Marco Saitta , Paolo V. Giaquinta

Several methods in nonadiabatic molecular dynamics are based on Madelung's hydrodynamic description of nuclear motion, while the electronic component is treated as a finite-dimensional quantum system. In this context, the quantum potential…

Mathematical Physics · Physics 2024-06-04 François Gay-Balmaz , Cesare Tronci

While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure. Phenotypic changes exhibited in cellular images are also indications of the…

Computer Vision and Pattern Recognition · Computer Science 2019-03-18 Philip T. Jackson , Yinhai Wang , Sinead Knight , Hongming Chen , Thierry Dorval , Martin Brown , Claus Bendtsen , Boguslaw Obara

The dynamical cluster-decay model (DCM) is developed further for the decay of hot and rotating compound nuclei (CN) formed in light heavy-ion reactions. The model is worked out in terms of only one parameter, namely the neck-length…

Nuclear Experiment · Physics 2008-11-26 Raj K. Gupta , M. Balasubramaniam , Rajesh Kumar , Dalip Singh , C. Beck , W. Greiner

Scatter can account for large errors in cone-beam CT (CBCT) due to its wide field of view, and its complicated nature makes its compensation difficult. Iterative polyenergetic reconstruction algorithms offer the potential to provide…

Medical Physics · Physics 2020-01-13 Jonathan H. Mason , Alessandro Perelli , William H. Nailon , Mike E. Davies

We calculate $^3$He+$p$ scattering phase shifts in two different microscopic cluster models, Model T and Model C, in order to show the effects of tensor force as well as $D$-wave components in the cluster wave function. Model T employs a…

Nuclear Theory · Physics 2014-11-18 K. Arai , S. Aoyama , Y. Suzuki

Flow matching models have shown great potential in image generation tasks among probabilistic generative models. However, most flow matching models in the literature do not explicitly utilize the underlying clustering structure in the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Anirban Samaddar , Yixuan Sun , Viktor Nilsson , Sandeep Madireddy

Text-to-image diffusion models enable high-quality image generation but are computationally expensive. While prior work optimizes per-inference efficiency, we explore an orthogonal approach: reducing redundancy across correlated prompts.…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Dale Decatur , Thibault Groueix , Wang Yifan , Rana Hanocka , Vladimir Kim , Matheus Gadelha

The large-area synthesis of high-crystalline-quality two-dimensional (2D) materials is at the core of novel material integration for semiconductor technology. This effort relies on developing fabrication and characterization techniques that…

This paper presents a novel structure-preserving scheme for Euler equations, focusing on the numerical conservation of entropy and kinetic energy. Explicit flux functions engineered to conserve entropy are introduced within the…

Numerical Analysis · Mathematics 2025-05-20 Kunal Bahuguna , Ramesh Kolluru , S. V. Raghurama Rao

Quantum embedding schemes have the potential to significantly reduce the computational cost of first principles calculations, whilst maintaining accuracy, particularly for calculations of electronic excitations in complex systems. In this…

Materials Science · Physics 2022-03-10 Joseph C. A. Prentice

Due to limited evidence and complex causes of regional climate change, the confidence in predicting fluvial floods remains low. Understanding the fundamental mechanisms intrinsic to geo-spatiotemporal information is crucial to improve the…

Machine Learning · Computer Science 2021-02-10 Aishwarya Sarkar , Jien Zhang , Chaoqun Lu , Ali Jannesari

Elastic-scattering phase shifts for four-nucleon systems are studied in an $ab$-$initio$ type cluster model in order to clarify the role of the tensor force and to investigate cluster distortions in low energy $d+d$ and $t+p$ scattering. In…

Nuclear Theory · Physics 2015-05-28 S. Aoyama , K. Arai , Y. Suzuki , P. Descouvemont , D. Baye
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