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Related papers: The structure of conservative gradient fields

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Modern problems in AI or in numerical analysis require nonsmooth approaches with a flexible calculus. We introduce generalized derivatives called conservative fields for which we develop a calculus and provide representation formulas.…

Optimization and Control · Mathematics 2020-04-10 Jérôme Bolte , Edouard Pauwels

Subgradient and Newton algorithms for nonsmooth optimization require generalized derivatives to satisfy subtle approximation properties: conservativity for the former and semismoothness for the latter. Though these two properties originate…

Optimization and Control · Mathematics 2021-02-18 Damek Davis , Dmitriy Drusvyatskiy

Using a geometric argument, we show that under a reasonable continuity condition, the Clarke subdifferential of a semi-algebraic (or more generally stratifiable) directionally Lipschitzian function admits a simple form: the normal cone to…

Optimization and Control · Mathematics 2012-11-16 Dmitriy Drusvyatskiy , Alexander D. Ioffe , Adrian S. Lewis

Using the notion of conservative gradient, we provide a simple model to estimate the computational costs of the backward and forward modes of algorithmic differentiation for a wide class of nonsmooth programs. The overhead complexity of the…

Numerical Analysis · Mathematics 2023-02-07 Jérôme Bolte , Ryan Boustany , Edouard Pauwels , Béatrice Pesquet-Popescu

Drifting models have recently gained attention for generating high-quality samples in a single forward pass. During training, they learn a push-forward map by following a vector-valued field, the drift field. We ask whether this procedure…

Machine Learning · Computer Science 2026-05-11 Leonard T. Franz , Sebastian Hoffmann , Tim Weiland , Bernhard Schölkopf , Georg Martius

In this paper, we consider the use of discrete gradients for differential-algebraic equations (DAEs) with a conservation/dissipation law. As one of the most popular numerical methods for conservative/dissipative ordinary differential…

Numerical Analysis · Mathematics 2018-05-15 Shun Sato

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

While conservation laws in gradient flow training dynamics are well understood for (mostly shallow) ReLU and linear networks, their study remains largely unexplored for more practical architectures. This paper bridges this gap by deriving…

Machine Learning · Computer Science 2025-06-09 Sibylle Marcotte , Rémi Gribonval , Gabriel Peyré

We characterize conservative median algebras and semilattices by means of forbidden substructures and by providing their representation as chains. Moreover, using a dual equivalence between median algebras and certain topological…

Rings and Algebras · Mathematics 2016-02-15 Miguel Couceiro , Jean-Luc Marichal , Bruno Teheux

We study whether iterated vector fields (vector fields composed with themselves) are conservative. We give explicit examples of vector fields for which this self-composition preserves conservatism. Notably, this includes gradient vector…

Optimization and Control · Mathematics 2021-11-16 Zachary Charles , Keith Rush

The convergence theory for the gradient sampling algorithm is extended to directionally Lipschitz functions. Although directionally Lipschitz functions are not necessarily locally Lipschitz, they are almost everywhere differentiable and…

Optimization and Control · Mathematics 2021-07-13 James V. Burke , Qiuying Lin

The convergence of stochastic interacting particle systems in the mean-field limit to solutions of conservative stochastic partial differential equations is established, with optimal rate of convergence. As a second main result, a…

Probability · Mathematics 2022-12-15 Benjamin Gess , Rishabh S. Gvalani , Vitalii Konarovskyi

It is well-known that the convergence of a family of smooth functions does not imply the convergence of its gradients. In this work, we show that if the family is definable in an o-minimal structure (for instance semialgebraic, subanalytic,…

Optimization and Control · Mathematics 2026-02-17 Sholom Schechtman

We introduce real vector spaces composed of set-valued maps on an open set. They are also complete metric spaces, lattices, commutative rings. The set of differentiable functions is a dense subset of these spaces and the classical gradient…

Optimization and Control · Mathematics 2007-05-23 Serguei Samborski

We present a scalable approach for semi-supervised learning on graph-structured data that is based on an efficient variant of convolutional neural networks which operate directly on graphs. We motivate the choice of our convolutional…

Machine Learning · Computer Science 2017-02-23 Thomas N. Kipf , Max Welling

The discrete gradient methods are integrators designed to preserve invariants of ordinary differential equations. From a formal series expansion of a subclass of these methods, we derive conditions for arbitrarily high order. We derive…

Numerical Analysis · Mathematics 2022-01-19 Sølve Eidnes

We show for a variety of classes of conservative PDEs that discrete gradient methods designed to have a conserved quantity (here called energy) also have a time-discrete conservation law. The discrete conservation law has the same conserved…

Numerical Analysis · Mathematics 2013-02-20 Robert I McLachlan , G R W Quispel

The conservation laws for a class of nonlinear equations with variable coefficients on discrete and noncommutative spaces are derived. For discrete models the conserved charges are constructed explicitly. The applications of the general…

Mathematical Physics · Physics 2007-05-23 M. Klimek

The goal and the main result of the paper is to provide a complete description of the field of rational differential invariants of one class of second order ordinary differential equations with scalar control parameter with respect to Lie…

Analysis of PDEs · Mathematics 2015-06-26 D. S. Gritsenko , O. M. Kiriukhin

Categorical skew lattices are a variety of skew lattices on which the natural partial order is especially well behaved. While most skew lattices of interest are categorical, not all are. They are characterized by a countable family of…

Rings and Algebras · Mathematics 2012-10-18 Michael Kinyon , Jonathan Leech
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