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Neural ordinary differential equations (ODEs) have attracted much attention as continuous-time counterparts of deep residual neural networks (NNs), and numerous extensions for recurrent NNs have been proposed. Since the 1980s, ODEs have…

Machine Learning · Computer Science 2022-10-17 Kazuki Irie , Francesco Faccio , Jürgen Schmidhuber

The development of efficient and robust dynamic models is fundamental in the field of systems and control engineering. In this paper, a new formulation for the dynamic model of nonlinear mechanical systems, that can be applied to different…

Systems and Control · Electrical Eng. & Systems 2026-02-09 Davide Tebaldi , Roberto Zanasi

Natural orbital theory is a computationally useful approach to the few and many-body quantum problem. While natural orbitals are known and applied since many years in electronic structure applications, their potential for time-dependent…

Atomic Physics · Physics 2014-10-08 J. Rapp , M. Brics , D. Bauer

Robotics is shifting from rigid, articulated systems to more sophisticated and heterogeneous mechanical structures. Soft robots, for example, have continuously deformable elements capable of large deformations. The flourishing of control…

Robotics · Computer Science 2025-03-13 Pietro Pustina , Cosimo Della Santina , Alessandro De Luca

A system of reduced equations is proposed for the electron motion in the strongly-radiation dominated regime for an arbitrary electromagnetic field configuration. The developed approach is used to analyze various scenarios of an electron…

Plasma Physics · Physics 2023-01-06 A. S. Samsonov , E. N. Nerush , I. Yu. Kostyukov

Discontinuous time derivatives are used to model threshold-dependent switching in such diverse applications as dry friction, electronic control, and biological growth. In a continuous flow, a discon- tinuous derivative can generate multiple…

Dynamical Systems · Mathematics 2013-06-18 Mike R. Jeffrey

Weighted finite-state machines are a fundamental building block of NLP systems. They have withstood the test of time -- from their early use in noisy channel models in the 1990s up to modern-day neurally parameterized conditional random…

Computation and Language · Computer Science 2023-09-29 Ran Zmigrod , Tim Vieira , Ryan Cotterell

In this paper, a multi-class Aw-Rascle \textrm{(AR)} model with time fractional order derivative is presented. The conservative form of the proposed model is considered for the natural extension and generalization of equations involved. The…

Analysis of PDEs · Mathematics 2024-05-17 Josephine Nanyondo , Joseph Y. T. Mugisha , Henry Kasumba

The appearance of the time derivative of the acceleration in the equation of motion (EOM) of an electric charge is studied. It is shown that when an electric charge is accelerated, a stress force exists in the curved electric field of the…

Classical Physics · Physics 2022-10-12 Amos Harpaz , Noam Soker

A description of the motion in noninertial reference frames by means of the inclusion of high time derivatives is studied. Incompleteness of the description of physical reality is a problem of any theory, both in quantum mechanics and…

General Physics · Physics 2020-01-01 Timur F. Kamalov

First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iteratively the learning rate for each coordinate. Despite great…

Machine Learning · Computer Science 2019-10-01 André Belotto da Silva , Maxime Gazeau

We discuss an elementary derivation of variational symmetries and corresponding integrals of motion for the Lagrangian systems depending on acceleration. Providing several examples, we make the manuscript accessible to a wide range of…

Mathematical Physics · Physics 2023-07-18 Ege Coban , Ilmar Gahramanov , Dilara Kosva

Model-based Reinforcement Learning and Control have demonstrated great potential in various sequential decision making problem domains, including in robotics settings. However, real-world robotics systems often present challenges that limit…

Machine Learning · Computer Science 2023-10-24 Achkan Salehi , Steffen Rühl , Stephane Doncieux

The invariance theorems obtained in analytical mechanics and derived from Noether's theorems can be adapted to fluid mechanics. For this purpose, it is useful to give a functional representation of the fluid motion and to interpret the…

Mathematical Physics · Physics 2023-04-10 Henri Gouin

Continuous-time trajectory representation has recently gained popularity for tasks where the fusion of high-frame-rate sensors and multiple unsynchronized devices is required. Lie group cumulative B-splines are a popular way of representing…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Christiane Sommer , Vladyslav Usenko , David Schubert , Nikolaus Demmel , Daniel Cremers

In recent years, soft robotics simulators have evolved to offer various functionalities, including the simulation of different material types (e.g., elastic, hyper-elastic) and actuation methods (e.g., pneumatic, cable-driven, servomotor).…

Robotics · Computer Science 2025-02-03 Etienne Ménager , Louis Montaut , Quentin Le Lidec , Justin Carpentier

Exponential time differencing methods is a power tool for high-performance numerical simulation of computationally challenging problems in condensed matter physics, fluid dynamics, chemical and biological physics, where mathematical models…

Numerical Analysis · Mathematics 2024-10-15 Evelina V. Permyakova , Denis S. Goldobin

Analytic first and second derivatives of the energy are developed for the fragment molecular orbital method interfaced with molecular mechanics in the electrostatic embedding scheme at the level of Hartree-Fock and density functional…

Chemical Physics · Physics 2020-05-19 Hiroya Nakata , Dmitri G. Fedorov

The linearization of the equations of motion of a robotics system about a given state-input trajectory, including a controlled equilibrium state, is a valuable tool for model-based planning, closed-loop control, gain tuning, and state…

Robotics · Computer Science 2022-04-20 Martijn Bos , Silvio Traversaro , Daniele Pucci , Alessandro Saccon

Mobile robots, such as ground vehicles and quadrotors, are becoming increasingly important in various fields, from logistics to agriculture, where they automate processes in environments that are difficult to access for humans. However, to…

Robotics · Computer Science 2025-10-08 Shao-Yi Yu , Jen-Wei Wang , Maya Horii , Vikas Garg , Tarek Zohdi