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We propose a physics-augmented neural network (PANN) framework for finite strain incompressible viscoelasticity within the generalized standard materials theory. The formulation is based on the multiplicative decomposition of the…

Computational Engineering, Finance, and Science · Computer Science 2025-11-06 Karl A. Kalina , Jörg Brummund , Markus Kästner

Underwater fish detection (UFD) remains a challenging task in computer vision due to low object resolution, significant background interference, and high visual similarity between targets and surroundings. Existing approaches primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Jinsong Yang , Zeyuan Hu , Yichen Li

We introduce a novel architecture and computational framework for formal, automated analysis of systems with a broad set of nonlinearities in the feedback loop, such as neural networks, vision controllers, switched systems, and even simple…

Optimization and Control · Mathematics 2018-05-02 Ivan Papusha , Ufuk Topcu , Steven Carr , Niklas Lauffer

We consider linear dynamical systems under floating-point rounding. In these systems, a matrix is repeatedly applied to a vector, but the numbers are rounded into floating-point representation after each step (i.e., stored as a…

Logic in Computer Science · Computer Science 2023-01-30 Engel Lefaucheux , Joël Ouaknine , David Purser , Mohammadamin Sharifi

In this article, we consider the general problem of checking the correctness of matrix multiplication. Given three $n \times n$ matrices $A$, $B$, and $C$, the goal is to verify that $A \times B=C$ without carrying out the computationally…

Data Structures and Algorithms · Computer Science 2017-05-31 Hao Ji , Michael Mascagni , Yaohang Li

Formal reasoning and automated theorem proving constitute a challenging subfield of machine learning, in which machines are tasked with proving mathematical theorems using formal languages like Lean. A formal verification system can check…

Artificial Intelligence · Computer Science 2025-11-05 Azim Ospanov , Farzan Farnia , Roozbeh Yousefzadeh

Recent efforts for improving the performance of neural network (NN) accelerators that meet today's application requirements have given rise to a new trend of logic-based NN inference relying on fixed function combinational logic. Mapping…

Hardware Architecture · Computer Science 2022-08-02 Soheil Nazar Shahsavani , Arash Fayyazi , Mahdi Nazemi , Massoud Pedram

This study uses stacked generalization, which is a two-step process of combining machine learning methods, called meta or super learners, for improving the performance of algorithms in step one (by minimizing the error rate of each…

Machine Learning · Computer Science 2020-04-07 Kathleen Kerwin , Nathaniel D. Bastian

Deadlock detection is a challenging issue in the analysis and design of on-chip networks. We have designed an algorithm to detect deadlocks automatically in on-chip networks with wormhole switching. The algorithm has been specified and…

Logic in Computer Science · Computer Science 2011-10-24 Freek Verbeek , Julien Schmaltz

There is a growing interest in the use of reduced-precision arithmetic, exacerbated by the recent interest in artificial intelligence, especially with deep learning. Most architectures already provide reduced-precision capabilities (e.g.,…

Hardware Architecture · Computer Science 2022-12-09 Olivier Sentieys , Daniel Menard

We present a new algorithm for estimating the star discrepancy of arbitrary point sets. Similar to the algorithm for discrepancy approximation of Winker and Fang [SIAM J. Numer. Anal. 34 (1997), 2028--2042] it is based on the optimization…

Data Structures and Algorithms · Computer Science 2021-09-21 Michael Gnewuch , Magnus Wahlström , Carola Winzen

Automatic fault detection (AFD) is a key technology to optimize the Operation and Maintenance of photovoltaic (PV) systems portfolios. A very common approach to detect faults in PV systems is based on the comparison between measured and…

Systems and Control · Electrical Eng. & Systems 2022-03-03 Eduardo Abdon Sarquis Filho , Björn Müller , Nicolas Holland , Christian Reise , Klaus Kiefer , Bernd Kollosch , Paulo J. Costa Branco

Probabilistic pushdown automata (pPDA) are a standard model for discrete probabilistic programs with procedures and recursion. In pPDA, many quantitative properties are characterized as least fixpoints of polynomial equation systems. In…

Formal Languages and Automata Theory · Computer Science 2023-02-28 Tobias Winkler , Joost-Pieter Katoen

Visibly pushdown automata (VPA), introduced by Alur and Madhusuan in 2004, is a subclass of pushdown automata whose stack behavior is completely determined by the input symbol according to a fixed partition of the input alphabet. Since its…

Formal Languages and Automata Theory · Computer Science 2009-11-18 Nguyen Van Tang

In todays world, high-power computing applications such as image processing, digital signal processing, graphics, and robotics require enormous computing power. These applications use matrix operations, especially matrix multiplication.…

Hardware Architecture · Computer Science 2019-10-29 Arish S , R. K. Sharma

Annotated data is an essential ingredient in natural language processing for training and evaluating machine learning models. It is therefore very desirable for the annotations to be of high quality. Recent work, however, has shown that…

Computation and Language · Computer Science 2022-09-27 Jan-Christoph Klie , Bonnie Webber , Iryna Gurevych

The discrete dipole approximation (DDA) is a widely used and versatile numerical method for solving electromagnetic scattering by arbitrarily shaped objects. Despite its popularity, quantitative comparisons between independent…

Computational Physics · Physics 2026-05-13 Clément Argentin , Patrick C. Chaumet , Michel Gross , Maxim A. Yurkin

Minimization of computational errors in the fixed-point data path is often difficult task. Many signal processing algorithms use chains of consecutive additions. The analyzing technique that can be applied to fixed-point data path synthesis…

Hardware Architecture · Computer Science 2013-08-01 Ilya Y. Zhbannikov , Gregory W. Donohoe

Modern programmable digital signal processing relies on floating-point numbers for their ease of use. Fixed-point number formats have the potential to save resources and improve execution time, but realising this potential burdens the…

Programming Languages · Computer Science 2024-03-12 Agathe Herrou , Florent de Dinechin , Stéphane Letz , Yann Orlarey , Anastasia Volkova

The design of embedded control systems is mainly done with model-based tools such as Matlab/Simulink. Numerical simulation is the central technique of development and verification of such tools. Floating-point arithmetic, that is well-known…

Programming Languages · Computer Science 2015-05-18 Alexandre Chapoutot
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