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We propose a novel approach to disentangle the generative factors of variation underlying a given set of observations. Our method builds upon the idea that the (unknown) low-dimensional manifold underlying the data space can be explicitly…

Machine Learning · Computer Science 2021-10-05 Marco Fumero , Luca Cosmo , Simone Melzi , Emanuele Rodolà

The use of deductive techniques, such as theorem provers, has several advantages in safety verification of hybrid sys- tems; however, state-of-the-art theorem provers require ex- tensive manual intervention. Furthermore, there is often a…

Logic in Computer Science · Computer Science 2021-09-08 Nikos Arechiga , James Kapinski , Jyotirmoy Deshmukh , Andre Platzer , Bruce Krogh

Invariant manifolds provide the geometric structures for describing and understanding dynamics of nonlinear systems. The theory of invariant manifolds for both finite and infinite dimensional autonomous deterministic systems, and for…

Dynamical Systems · Mathematics 2007-05-23 Jinqiao Duan , Kening Lu , Bjoern Schmalfuss

Learning-based models for fluid dynamics often operate in unconstrained function spaces, leading to physically inadmissible, unstable simulations. While penalty-based methods offer soft regularization, they provide no structural guarantees,…

Machine Learning · Computer Science 2026-03-26 Xigui Li , Hongwei Zhang , Ruoxi Jiang , Deshu Chen , Chensen Lin , Limei Han , Yuan Qi , Xin Guo , Yuan Cheng

Deep neural networks (DNN) have shown great capacity of modeling a dynamical system; nevertheless, they usually do not obey physics constraints such as conservation laws. This paper proposes a new learning framework named ConCerNet to…

Machine Learning · Computer Science 2023-07-20 Wang Zhang , Tsui-Wei Weng , Subhro Das , Alexandre Megretski , Luca Daniel , Lam M. Nguyen

This paper introduces a differential dynamic programming (DDP) based framework for polynomial trajectory generation for differentially flat systems. In particular, instead of using a linear equation with increasing size to represent…

Optimization and Control · Mathematics 2021-09-13 Kun Cao , Muqing Cao , Shenghai Yuan , Lihua Xie

This paper explores a mathematical technique for deriving dynamical invariants (i.e. constants of motion) in time-dependent gravitational potentials. The method relies on the construction of a canonical transformation that removes the…

Astrophysics of Galaxies · Physics 2015-06-16 Jorge Peñarrubia

We introduce the notion of matrices graph, defining continued fraction algorithms where the past and the future are almost independent. We provide an algorithm to convert more general algorithms into matrices graphs. We present an algorithm…

Dynamical Systems · Mathematics 2023-11-17 Paul Mercat

Recent results in control systems and numerical integration literature utilize invariant set theory to lift dynamical systems evolving on nonlinear manifolds to those evolving on vector spaces. We leverage this technique to propose an…

Optimization and Control · Mathematics 2022-08-09 Siddharth H. Nair

Loop invariants are properties of a program loop that hold before and after each iteration of the loop. They are often employed to verify programs and ensure that algorithms consistently produce correct results during execution.…

Symbolic Computation · Computer Science 2024-05-16 Erdenebayar Bayarmagnai , Fatemeh Mohammadi , Rémi Prébet

Regression models with both high-dimensional responses and covariates have attracted growing attention. Standard multivariate regression models become inadequate when the response variables depend not only on observed covariates but also on…

Methodology · Statistics 2026-05-01 Jing Ouyang , Chengyu Cui , Yunxiao Chen , Kean Ming Tan , Gongjun Xu

In the context of convex optimization problems in Hilbert spaces, we induce inertial effects into the classical ADMM numerical scheme and obtain in this way so-called inertial ADMM algorithms, the convergence properties of which we…

Optimization and Control · Mathematics 2014-04-18 Radu Ioan Bot , Ernö Robert Csetnek

Efficiently estimating system dynamics from data is essential for minimizing data collection costs and improving model performance. This work addresses the challenge of designing future control inputs to maximize information gain, thereby…

Systems and Control · Electrical Eng. & Systems 2025-04-29 Joshua Ott , Mykel J. Kochenderfer , Stephen Boyd

The goal of invariant theory is to find all the generators for the algebra of representations of a group that leave the group invariant. Such generators will be called \emph{basic invariants}. In particular, we set out to find the set of…

General Topology · Mathematics 2011-10-26 Quinton Westrich

Synthesizing user-intended programs from a small number of input-output examples is a challenging problem with several important applications like spreadsheet manipulation, data wrangling and code refactoring. Existing synthesis systems…

Artificial Intelligence · Computer Science 2018-09-17 Ashwin Kalyan , Abhishek Mohta , Oleksandr Polozov , Dhruv Batra , Prateek Jain , Sumit Gulwani

The structural properties of graphs are usually characterized in terms of invariants, which are functions of graphs that do not depend on the labeling of the nodes. In this paper we study convex graph invariants, which are graph invariants…

Optimization and Control · Mathematics 2012-09-21 Venkat Chandrasekaran , Pablo A. Parrilo , Alan S. Willsky

In this paper we provide new methodology for inference of the geometric features of a multivariate density in deconvolution. Our approach is based on multiscale tests to detect significant directional derivatives of the unknown density at…

Methodology · Statistics 2016-11-21 Konstantin Eckle , Nicolai Bissantz , Holger Dette

We introduce a family of maps generating continued fractions where the digit $1$ in the numerator is replaced cyclically by some given non-negative integers $(N_1,\ldots,N_m)$. We prove the convergence of the given algorithm, and study the…

Dynamical Systems · Mathematics 2021-12-09 Karma Dajani , Niels Langeveld

We introduce the notion of porous invariants for multipath (or branching/nondeterministic) affine loops over the integers; these invariants are not necessarily convex, and can in fact contain infinitely many 'holes'. Nevertheless, we show…

Logic in Computer Science · Computer Science 2021-06-02 Engel Lefaucheux , Joël Ouaknine , David Purser , James Worrell

A representative set of fault diagnosis problems is formulated for linear time-invariant systems with additive faults. For all formulated problems, general existence conditions of their solutions are given. An overview of recent…

Systems and Control · Computer Science 2022-02-02 Andreas Varga
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