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In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our previous Self-Reference Deep Adaptive Curve Estimation (Self-DACE). To better address the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Jianyu Wen , Jun Xie , Feng Chen , Zhepeng Wang , Chenhao Wu , Tong Zhang , Yixuan Yu , Piotr Swierczynski

Hom-Lie algebras are generalizations of Lie algebras that arise naturally in the study of nonassociative algebraic structures. In this paper, the concepts of solvable and nilpotent Hom-Lie algebras studied further. In the theory of groups,…

Rings and Algebras · Mathematics 2023-05-02 Shadi Shaqaqha , Nadeen Kdaisat

A quasi-Lie scheme is a geometric structure that provides t-dependent changes of variables transforming members of an associated family of systems of first-order differential equations into members of the same family. In this note we…

Mathematical Physics · Physics 2013-03-27 José F. Cariñena , Partha Guha , Javier de Lucas

Lie symmetries of systems of second-order linear ordinary differential equations with constant coefficients are exhaustively described over both the complex and real fields. The exact lower and upper bounds for the dimensions of the maximal…

Classical Analysis and ODEs · Mathematics 2014-03-25 Vyacheslav M. Boyko , Roman O. Popovych , Nataliya M. Shapoval

Data analysis and performance evaluation of simulation deduction plays a pivotal role in modern warfare, which enables military personnel to gain invaluable insights into the potential effectiveness of different strategies, tactics, and…

Computation and Language · Computer Science 2025-11-17 Shansi Zhang , Min Li

We study a new class of infinite dimensional Lie algebras, which has important applications to the theory of integrable equations. The construction of these algebras is very similar to the one for automorphic functions and this motivates…

Mathematical Physics · Physics 2009-11-10 S. Lombardo , A. V. Mikhailov

While large language models (LLMs) are increasingly being used for program synthesis, they lack the global view needed to develop useful abstractions; they generally predict programs one at a time, often repeating the same functionality.…

Software Engineering · Computer Science 2024-06-07 Elias Stengel-Eskin , Archiki Prasad , Mohit Bansal

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

In this paper, the classical Lie symmetry analysis and the generalized form of Lie symmetry method are performed for a general short pulse equation. The point, contact and local symmetries for this equation are given. In this paper, we…

Analysis of PDEs · Mathematics 2021-08-16 Mehdi Nadjafikhah

Detailed dynamical systems models used in life sciences may include dozens or even hundreds of state variables. Models of large dimension are not only harder from the numerical perspective (e.g., for parameter estimation or simulation), but…

Quantitative Methods · Quantitative Biology 2022-07-06 Antonio Jiménez-Pastor , Joshua Paul Jacob , Gleb Pogudin

A constructive method for decomposing finite dimensional representations of semisimple real Lie algebras is developed. The method is illustrated by an example. We also discuss an implementation of the algorithm in the language of the…

Representation Theory · Mathematics 2020-06-19 Sajid Ali , Hassan Azad , Indranil Biswas , Willem A. de Graaf

Large number of ReLU and MAC operations of Deep neural networks make them ill-suited for latency and compute-efficient private inference. In this paper, we present a model optimization method that allows a model to learn to be shallow. In…

Machine Learning · Computer Science 2023-04-27 Souvik Kundu , Yuke Zhang , Dake Chen , Peter A. Beerel

High index differential algebraic equations (DAEs) are ordinary differential equations (ODEs) with constraints and arise frequently from many mathematical models of physical phenomenons and engineering fields. In this paper, we generalize…

Symbolic Computation · Computer Science 2015-04-21 Xiaolin Qin , Lu Yang , Yong Feng , Bernhard Bachmann , Peter Fritzson

We derive a method for finding Lie Symmetries for third-order difference equations. We use these symmetries to reduce the order of the difference equations and hence obtain the solutions of some third-order difference equations. We also…

Exactly Solvable and Integrable Systems · Physics 2017-01-25 S. Mamba , M. K. Folly-Gbetoula , A. H. Kara

Large language models (LLMs) usually fall short on information extraction (IE) tasks and struggle to follow the complex instructions of IE tasks. This primarily arises from LLMs not being aligned with humans, as mainstream alignment…

Computation and Language · Computer Science 2024-10-25 Yunjia Qi , Hao Peng , Xiaozhi Wang , Bin Xu , Lei Hou , Juanzi Li

Most commonly used non-linear machine learning methods are closed-box models, uninterpretable to humans. The field of explainable artificial intelligence (XAI) aims to develop tools to examine the inner workings of these closed boxes. An…

Machine Learning · Computer Science 2026-05-26 Lauri Seppäläinen , Mudong Guo , Kai Puolamäki

Studies in thermodynamics often require the reduction of some first or second order partial derivatives in terms of a smaller basic set. A simple algorithm to perform such a reduction is presented here, together with a review of earlier…

Computational Physics · Physics 2014-02-11 Jacques H. H. Perk

A non trivial application of a modern computer language ("C") in a highly structured and object-oriented fashion is presented. The contest is that of Lie algebra representations (irreps), specifically the problem of reducing the products of…

High Energy Physics - Theory · Physics 2008-02-03 Antonio Candiello

The reformulation-linearization technique (RLT) is a prominent approach to constructing tight linear relaxations of non-convex continuous and mixed-integer optimization problems. The goal of this paper is to extend the applicability and…

Optimization and Control · Mathematics 2024-07-22 Ksenia Bestuzheva , Ambros Gleixner , Tobias Achterberg

Solving systems of ordinary differential equations (ODEs) is essential when it comes to understanding the behavior of dynamical systems. Yet, automated solving remains challenging, in particular for nonlinear systems. Computer algebra…

Machine Learning · Computer Science 2025-06-25 Paul Kahlmeyer , Niklas Merk , Joachim Giesen