arXiv research

Gradient estimation techniques applied to programs with randomness in high energy physics.

This paper proposes a joint energy and data market to handle uncertainty in energy procurement.

Improved EEG event classification using differential energy.

Paper proposes new loss functions for training energy networks.

Discrete geometry model approximates Willmore energy.

Let X be a smooth manifold of dimension 1+n endowed with a lorentzian metric g, and let T be the electromagnetic energy tensor associated to a 2-form F. In this paper we characterize this tensor T as the only 2-covariant natural tensor associated to a lorentzian metric and a 2-form that is independent of the unit of sc…

New method learns latent energy models using particle algorithms.

DeepONet learns operators for PDEs with varying parameters and initial conditions.

Novel method for solving ODEs on k-polysymplectic manifolds.

Study inextensible flows of curves in 4D pseudo-Galilean space and defines energy functions.

Finite energy solutions of 4-harmonic and ES-4-harmonic maps are trivial.

Quantum vacuum energy (Casimir energy) is reviewed for a mathematical audience as a topic in spectral theory. Then some one-dimensional systems are solved exactly, in terms of closed classical paths and periodic orbits. The relations among local spectral densities, energy densities, global eigenvalue densities, and tot…

Study on energy storage's impact on electricity prices and profitability.

Stella Nera accelerates matrix multiplications with a hash-based approach, achieving high energy efficiency and accuracy.

We derive necessary conditions for the spinorial Witten-Nester energy to be well-defined for asymptotically locally AdS spacetimes. We find that the conformal boundary should admit a spinor satisfying certain differential conditions and in odd dimensions the boundary metric should be conformally Einstein. We show that …

Harmonic extension of Weil-Petersson circle homeomorphisms

Modeling wind dynamics in Saudi Arabia using deep learning and stochastic PDEs.

New method uses nearest neighbors quantile filter for probabilistic energy forecasting.

Paper finds relations between Willmore-type energies, weighted areas, and vertical potential energies for cylindrical critical points.

Study of phase separation and geometry on a closed elastic curve, including dynamics and free energy minimization.

The study extends calibrated geometry to smooth maps and finds energy bounds.

A new training method for normalizing flows without samples.

Gradient flow studies Spin(7)-structures on compact 8-manifolds.

We study some analytical and geometric properties of a two-dimensional nonlinear sigma model with gravitino which comes from supersymmetric string theory. When the action is critical w.r.t. variations of the various fields including the gravitino, there is a symmetric, traceless and divergence-free energy-momentum tens…

Neural ODEs control graph dynamics with low energy feedback.

The fundamental properties of $J$-holomorphic maps depend on two inequalities: The gradient inequality gives a pointwise bound on the differential of a $J$-holomorphic map in terms of its energy. The cylinder inequality stipulates and quantifies the exponential decay of energy along cylinders of small total energy. We …

Proves smooth critical points of Möbius energy are analytic.

The paper controls complex systems using energy-based methods.

CR-harmonic maps defined for pseudoconvex manifolds.

We prove the energy identity for min-max sequences of the Sacks-Uhlenbeck and the biharmonic approximation of harmonic maps from surfaces into general target manifolds. The proof relies on Hopf-differential type estimates for the two approximations and on estimates for the concentration radius of bubbles.

We show the existence of a thick thin decomposition of the domain of a pseudo holomorphic curve with boundary. The geometry of the thick part is bounded uniformly in the energy. Furthermore, in the thick part, there is a uniform bound on the differential which is exponential in the energy. The thin part consists of ann…

Proposes linking energy and force uncertainty in deep learning potentials.

Gradient flows for knot energies ensure long-term existence of knotted loops.

Model predicts BESS interactions and price impacts in energy markets.

This note is to concern a generalization to the case of twisted coefficients of the classical theory of Abelian differentials on a compact Riemann surface. We apply the Dirichlet's principle to a modified energy functional to show the existence of differentials with twisted coefficients of the second and third kinds un…

3D object detection improved using energy-based models.

In this paper we develop a Morse theory for the uniform energy. We use the one-sided directional derivative of the distance function to study the minimizing properties of variations through closed geodesics. This derivative is then used to define a one-sided directional derivative for the uniform energy which allows us…

A deep learning method solves nonlinear filtering problems efficiently.

Differential conservation laws in Lagrangian field theory are usually related to symmetries of a Lagrangian density and are obtained if the Lie derivative of a Lagrangian density by a certain class of vector fields on a fiber bundle vanishes. However, only two field models meet this property in fact. In gauge theory of…

Probabilistic models can be defined by an energy function, where the probability of each state is proportional to the exponential of the state's negative energy. This paper considers a generalization of energy-based models in which the probability of a state is proportional to an arbitrary positive, strictly decreasing…

Paper introduces a modified Allen-Cahn equation for better energy equipartition.

Paper extends multivariate rank tests for robust subspace detection.

We describe the space of measured foliations induced on a compact Riemann surface by meromorphic quadratic differentials. We prove that any such foliation is realized by a unique such differential $q$ if we prescribe, in addition, the principal parts of $\sqrt q$ at the poles. This generalizes a theorem of Hubbard and …

We use matricial free energy to regularize autoencoders, producing Gaussian-like codes.

We consider variation of energy of the light-like particle in Riemann space-time, find lagrangian, canonical momenta and forces. Equations of the critical curve are obtained by the nonzero energy integral variation in accordance with principles of the calculus of variations in mechanics. This method is shown to not lea…

Paper introduces a neural framework for accurate energy forecasting.

In this paper we study 1/k-geodesics, those closed geodesics that minimize on any subinterval of length $l(γ)/k$. We employ energy methods to provide a relationship between the 1/k-geodesics and what we define as the balanced points of the uniform energy. We show that classes of balanced points of the uniform energy pe…

Study the energy spectrum of metrics on surfaces and its relation to simple length spectrum.