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We propose to calculate inelastic response functions from the inversion of their integral transform with a Lorentz kernel. The transform can be obtained using bound-state type methods. Thus one does not need to solve the much more…

Nuclear Theory · Physics 2009-10-28 Victor D. Efros , Winfried Leidemann , Giuseppina Orlandini

The ability of deep networks to learn superior representations hinges on leveraging the proper inductive biases, considering the inherent properties of datasets. In tabular domains, it is critical to effectively handle heterogeneous…

Machine Learning · Computer Science 2024-05-15 Kyungeun Lee , Ye Seul Sim , Hye-Seung Cho , Moonjung Eo , Suhee Yoon , Sanghyu Yoon , Woohyung Lim

New developments have been brought to our energy-, spin- and parity-dependent nuclear level densities based on the microscopic combinatorial method. Our new calculation is based on the BSkG3 mean-field model which relies on a…

Nuclear Theory · Physics 2026-01-08 S. Goriely , W. Ryssens , S. Hilaire , A. J. Koning

This paper considers the non-linear inverse problem of reconstructing an electric conductivity distribution from the interior power density in a bounded domain. Applications include the novel tomographic method known as acousto-electric…

Optimization and Control · Mathematics 2018-08-29 B. J. Adesokan , Kim Knudsen , Venkateswaran P. Krishnan , Souvik Roy

This paper presents a spike-based model which employs neurons with functionally distinct dendritic compartments for classifying high dimensional binary patterns. The synaptic inputs arriving on each dendritic subunit are nonlinearly…

Neural and Evolutionary Computing · Computer Science 2014-11-26 Shaista Hussain , Shih-Chii Liu , Arindam Basu

The classical models for irreversible diffusion-influenced reactions can be derived by introducing absorbing boundary conditions to over-damped continuous Brownian motion (BM) theory. As there is a clear corresponding stochastic process,…

Statistical Mechanics · Physics 2016-10-13 Mauricio J. Del Razo , Hong Qian

The basis-set correction method based on density-functional theory consists in correcting the energy calculated by a wave-function method with a given basis set by a density functional. This basis-set correction density functional…

Chemical Physics · Physics 2023-07-05 Diata Traore , Emmanuel Giner , Julien Toulouse

The Gridding algorithm has shown great utility for reconstructing images from non-uniformly spaced samples in the Fourier domain in several imaging modalities. Due to the non-uniform spacing, some correction for the variable density of the…

Image and Video Processing · Electrical Eng. & Systems 2021-06-17 Nicholas Dwork , Daniel O'Connor , Ethan M. I. Johnson , Corey A. Baron , Jeremy W. Gordon , John M. Pauly , Peder E. Z. Larson

In this paper, we develop the residual based a posteriori error estimates and the corresponding adaptive mesh refinement algorithm for atomistic/continuum (a/c) coupling with finite range interactions in two dimensions. We have…

Numerical Analysis · Mathematics 2018-07-02 Mingjie Liao , Ping Lin , Lei Zhang

The recently introduced Matching by Tone Mapping (MTM) dissimilarity measure enables template matching under smooth non-linear distortions and also has a well-established mathematical background. MTM operates by binning the template, but…

Machine Learning · Computer Science 2020-07-27 Attila Fazekas , György Kovács

We apply the iterative nonlinear programming method, previously proposed in our earlier work, to optimize Schur test functions and thereby provide refined upper bounds for the norms of integral operators. As an illustration, we derive such…

Optimization and Control · Mathematics 2025-10-08 Mikhail Anikushin , Andrey Romanov

The Poisson-Boltzmann equation is a widely used model to study the electrostatics in molecular solvation. Its numerical solution using a boundary integral formulation requires a mesh on the molecular surface only, yielding accurate…

Numerical Analysis · Mathematics 2020-09-25 Vicente Ramm , Jehanzeb H. Chaudhry , Christopher D. Cooper

Low-bit width neural networks have been extensively explored for deployment on edge devices to reduce computational resources. Existing approaches have focused on gradient-based optimization in a two-stage train-and-compress setting or as a…

Machine Learning · Computer Science 2022-06-07 Han Zhou , Aida Ashrafi , Matthew B. Blaschko

The distributed operating room (OR) scheduling problem aims to find an assignment of surgeries to ORs across collaborating hospitals that share their waiting lists and ORs. We propose a stochastic extension of this problem where surgery…

Optimization and Control · Mathematics 2020-10-06 Cheng Guo , Merve Bodur , Dionne M. Aleman , David R. Urbach

In computer vision and machine learning, a crucial challenge is to lower the computation and memory demands for neural network inference. A commonplace solution to address this challenge is through the use of binarization. By binarizing the…

Machine Learning · Computer Science 2023-07-06 Guy Berger , Aviv Navon , Ethan Fetaya

We deal with the shape reconstruction of inclusions in elastic bodies. For solving this inverse problem in practice, data fitting functionals are used. Those work better than the rigorous monotonicity methods from [5], but have no…

Numerical Analysis · Mathematics 2022-12-13 Sarah Eberle , Bastian Harrach

We introduce a new relativistic energy density functional constrained by the ground state properties of atomic nuclei along with the isoscalar giant monopole resonance energy and dipole polarizability in $^{208}$Pb. A unified framework of…

Nuclear Theory · Physics 2019-03-27 E. Yuksel , T. Marketin , N. Paar

We solve by Chebyshev spectral collocation some genuinely nonlinear Liouville-Bratu-Gelfand type, 1D and a 2D boundary value problems. The problems are formulated on the square domain $[-1, 1]\times[-1, 1]$ and the boundary condition…

Numerical Analysis · Mathematics 2020-11-30 Calin-Ioan Gheorghiu

Nonlocal kinetic energy density functionals (KEDFs) with density-dependent kernels are currently the most accurate functionals available for orbital-free density functional theory (OF-DFT) calculations. However, despite advances in…

Materials Science · Physics 2024-12-05 Yongshuo Chen , Cheng Ma , Boning Cui , Tian Cui , Wenhui Mi , Qiang Xu , Yanchao Wang , Yanming Ma

We reexamine the recently introduced basis-set correction theory based on density-functional theory consisting in correcting the basis-set incompleteness error of wave-function methods using a density functional. We use a one-dimensional…

Chemical Physics · Physics 2022-02-16 Diata Traore , Emmanuel Giner , Julien Toulouse