English
Related papers

Related papers: Selecting 3D Chaotic Flow States for Accelerated D…

200 papers

Recent efforts have extended the flow-matching framework to discrete generative modeling. One strand of models directly works with the continuous probabilities instead of discrete tokens, which we colloquially refer to as Continuous-State…

Machine Learning · Computer Science 2025-04-15 Chaoran Cheng , Jiahan Li , Jiajun Fan , Ge Liu

The Cahn-Hilliard equation with an externally-prescribed chaotic shear flow is studied in two and three dimensions. The main goal is to compare and contrast the phase separation in two and three dimensions, using high-resolution numerical…

Fluid Dynamics · Physics 2014-12-23 Lennon O'Naraigh , Selma Shun , Aurore Naso

Identifying low-energy adsorption geometries on catalytic surfaces is a practical bottleneck for computational heterogeneous catalysis: the difficulty lies not only in the cost of density functional theory (DFT) but in proposing initial…

Machine Learning · Computer Science 2026-02-24 Jiangjie Qiu , Wentao Li , Honghao Chen , Leyi Zhao , Xiaonan Wang

A new three dimensional approach to the chaos game representation of protein sequences is explored in this thesis. The basics of DNA, the synthesis of proteins from DNA, protein structure and functionality and sequence alignment techniques…

Biomolecules · Quantitative Biology 2023-03-20 Annie Thomas

Molecular motor proteins form the basis of cellular dynamics. Recently, notable efforts have led to the creation of their DNA-based mimics, which can carry out complex nanoscale motion. However, such functional analogues have not yet been…

Biological Physics · Physics 2021-05-14 Kerstin Goepfrich , Maximilian J. Urban , Christoph Frey , Ilia Platzman , Joachim P. Spatz , Na Liu

In recent years, Rectified flow (RF) has gained considerable popularity largely due to its generation efficiency and state-of-the-art performance. In this paper, we investigate the degree to which RF automatically adapts to the intrinsic…

Machine Learning · Statistics 2026-02-24 Saptarshi Roy , Alessandro Rinaldo , Purnamrita Sarkar

Central to our understanding of chemical reactivity is the principle of mass conservation, which is fundamental for ensuring physical consistency, balancing equations, and guiding reaction design. However, data-driven computational models…

Machine Learning · Computer Science 2025-02-19 Joonyoung F. Joung , Mun Hong Fong , Nicholas Casetti , Jordan P. Liles , Ne S. Dassanayake , Connor W. Coley

The conformational behavior of a giant DNA mediated by condensing agents in the bulk solution has been investigated through experimental and theoretical approaches. Experimentally, a pronounced conformational hysteresis is observed for…

Soft Condensed Matter · Physics 2009-11-13 Chwen-Yang Shew , Yuji Higuchi , Kenichi Yoshikawa

Image-based computational fluid dynamics (CFD) has emerged as a powerful tool to study cardiovascular flows while 2D echocardiography (echo) is the most widely used non-invasive imaging modality for diagnosis of heart disease. Here, echo is…

3D Particle Imaging Velocimetry (3D-PIV) aim to recover the flow field in a volume of fluid, which has been seeded with tracer particles and observed from multiple camera viewpoints. The first step of 3D-PIV is to reconstruct the 3D…

Computer Vision and Pattern Recognition · Computer Science 2018-05-23 Katrin Lasinger , Christoph Vogel , Thomas Pock , Konrad Schindler

Chemically reacting flows are common in engineering, such as hypersonic flow, combustion, explosions, manufacturing processes and environmental assessments. For combustion, the number of reactions can be significant (over 100) and due to…

Machine Learning · Computer Science 2021-04-06 Thomas S. Brown , Harbir Antil , Rainald Löhner , Fumiya Togashi , Deepanshu Verma

The recent advent of advanced microfabrication capabilities of microfluidic devices has driven attention towards the behavior of particles in inertial flows within microchannels for applications related to the separation and concentration…

Fluid Dynamics · Physics 2018-12-03 Mike Garcia , Sumita Pennathur

Most earlier 3D structure-based molecular generation approaches follow an atom-wise paradigm, incrementally adding atoms to a partially built molecular fragment within protein pockets. These methods, while effective in designing tightly…

In this work, we introduce an algorithmic approach to generate microvascular networks starting from larger vessels that can be reconstructed without noticeable segmentation errors. Contrary to larger vessels, the reconstruction of…

Computational Engineering, Finance, and Science · Computer Science 2020-07-10 Tobias Köppl , Ettore Vidotto , Barbara Wohlmuth

In equilibrium self-assembly, microscopic building blocks spontaneously self-organize into stable structures as dictated by their interaction potentials, which limits the accessible structural features to those that correspond to global…

Soft Condensed Matter · Physics 2026-04-17 Pepijn G. Moerman , Chenghung Chou , Thomas E. Videbæk , W. Benjamin Rogers , Rebecca Schulman

Complementary strands in DNA double helix show temporary fluctuational openings which are essential to biological functions such as transcription and replication of the genetic information. Such large amplitude fluctuations, known as the…

Biological Physics · Physics 2013-02-12 Marco Zoli

We extend the Balancing Domain Decomposition by Constraints (BDDC) method to flows in porous media discretised by mixed-hybrid finite elements with combined mesh dimensions. Such discretisations appear when major geological fractures are…

Numerical Analysis · Mathematics 2015-11-24 Jakub Šístek , Jan Březina , Bedřich Sousedík

Diffusion and flow matching approaches to generative modeling have shown promise in domains where the state space is continuous, such as image generation or protein folding & design, and discrete, exemplified by diffusion large language…

A generative model capable of sampling realistic molecules with desired properties could accelerate chemical discovery across a wide range of applications. Toward this goal, significant effort has focused on developing models that jointly…

Machine Learning · Computer Science 2025-08-19 Ian Dunn , David R. Koes

n this work, we propose a latent molecular diffusion model that can make the generated 3D molecules rich in diversity and maintain rich geometric features. The model captures the information of the forces and local constraints between atoms…

Machine Learning · Computer Science 2024-12-06 Xiang Chen
‹ Prev 1 4 5 6 7 8 10 Next ›