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Learning-based image harmonization techniques are usually trained to undo synthetic random global transformations applied to a masked foreground in a single ground truth photo. This simulated data does not model many of the important…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Ke Wang , Michaël Gharbi , He Zhang , Zhihao Xia , Eli Shechtman

The need for advanced materials has led to the development of complex, multi-component alloys or solid-solution alloys. These materials have shown exceptional properties like strength, toughness, ductility, electrical and electronic…

Hypothesis Emerging energy-related technologies deal with multiscale hierarchical structures, intricate surface morphology, non-axisymmetric interfaces, and complex contact lines where wetting is difficult to quantify with classical…

Fluid Dynamics · Physics 2021-08-24 Chenhao Sun , James McClure , Steffen Berg , Peyman Mostaghimi , Ryan T. Armstrong

We propose a new framework to compare alternative geostatistical descriptions of a given site. Multiple realizations of each of the considered geostatistical models and their corresponding tomograms (based on inversion of noise-contaminated…

Geophysics · Physics 2017-01-09 N. Linde , T. Lochbühler , M. Dogan , R. L. Van Dam

Rapid advancements in machine learning (ML) are transforming materials science by significantly speeding up material property calculations. However, the proliferation of ML approaches has made it challenging for scientists to keep up with…

Machine Learning · Computer Science 2024-07-12 Ali Ramlaoui , Théo Saulus , Basile Terver , Victor Schmidt , David Rolnick , Fragkiskos D. Malliaros , Alexandre Duval

Reconstructing real-world objects from multi-view images is essential for applications in 3D editing, AR/VR, and digital content creation. Existing methods typically prioritize either geometric accuracy (Multi-View Stereo) or photorealistic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Zhejia Cai , Puhua Jiang , Shiwei Mao , Hongkun Cao , Ruqi Huang

Machine learning models can assist with metamaterials design by approximating computationally expensive simulators or solving inverse design problems. However, past work has usually relied on black box deep neural networks, whose reasoning…

Machine Learning · Computer Science 2022-10-04 Zhi Chen , Alexander Ogren , Chiara Daraio , L. Catherine Brinson , Cynthia Rudin

We are witnessing a proliferation of textured 3D models captured from the real world with automatic photo-reconstruction tools. Digital 3D models of this class come with a unique set of characteristics and defects -- especially concerning…

Graphics · Computer Science 2020-12-29 Andrea Maggiordomo , Federico Ponchio , Paolo Cignoni , Marco Tarini

Electromagnetic metasurfaces have attracted significant interest recently due to their low profile and advantageous applications. Practically, many metasurface designs start with a set of constraints for the radiated far-field, such as…

Materials Science · Physics 2022-04-04 Stewart Pearson , Parinaz Naseri , Sean V. Hum

The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…

Materials Science · Physics 2021-10-04 Krishnendu Mukherjee , Alexander W. Dowling , Yamil Colón

Basket weaving is a traditional craft used to create practical three-dimensional (3D) structures. While the geometry and aesthetics of baskets have received considerable attention, the underlying mechanics and modern engineering potential…

Soft Condensed Matter · Physics 2025-07-02 Guowei Wayne Tu , Evgueni T. Filipov

Discrete mesoscale network models, in which explicitly modeled polymer chains are replaced by implicit pairwise potentials, are capable of predicting the macroscale mechanical response of polymeric materials such as elastomers and gels,…

Soft Condensed Matter · Physics 2024-07-16 Robert J. Wagner , Meredith N. Silberstein

Capturing and predicting the effective mechanical properties of highly porous cellular media still represents a significant challenge for the research community, due to their complex structural interdependencies and known size effects.…

Soft Condensed Matter · Physics 2024-07-30 Alexander Malik , Geralf Hütter , Martin Abendroth , Bjoern Kiefer

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving…

Computational Physics · Physics 2017-01-04 Huan Lei , Xiu Yang , Zhen Li , George Karniadakis

We present a geometric framework for the inverse design of smart woven fabrics composed of non-uniformly shrinking threads. A sufficiently tight weaving structure imposes strong local criteria on the material deformation and reduces the…

Soft Condensed Matter · Physics 2026-01-23 Einav Berin , Hillel Aharoni

We present a method for computing locally varying nonlinear mechanical properties in particle simulations of amorphous solids. Plastic rearrangements outside a probed region are suppressed by introducing an external field that directly…

Soft Condensed Matter · Physics 2023-07-18 Jörg Rottler , Céline Ruscher , Peter Sollich

Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible…

Computational Engineering, Finance, and Science · Computer Science 2024-03-21 Natascha Jeziorski , Claudia Redenbach

We consider problems related to initial meshing and adaptive mesh refinement for the electromagnetic simulation of various structures. The quality of the initial mesh and the performance of the adaptive refinement are of great importance…

A three-dimensional multi-scale computational homogenisation framework is developed for the prediction of nonlinear micro/meso-mechanical response of the fibre-reinforced polymer (FRP) composites. Two dominant damage mechanisms, i.e. matrix…

Computational Engineering, Finance, and Science · Computer Science 2016-10-18 Zahur Ullah , Lukasz Kaczmarczyk , Chris J. Pearce

This project is focused on investigating the structural performance of parts and structures produced using the latest additive manufacturing techniques. For additive manufacturing of test coupons, fused deposition modeling of…

Applied Physics · Physics 2025-03-25 Hunter Watts , Ryan Premo , Wayne Huberty , Chris Bounds , Han-Gyu Kim