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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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4795142189 · Jun 202019922001200920182026
48 results for minimum energy path

Gaussian process regression cuts energy evaluations for atomic rearrangement paths.

problem Reducing computational effort for minimum energy paths in complex systems.
method Gaussian process regression to approximate energy surfaces and converge to minimum energy paths.
result Significant reduction in energy evaluations (less than a fifth for a test problem).

Gaussian process regression speeds up nudged elastic band calculations for transitions.

problem Reducing computational effort for calculating minimum energy paths in thermalized systems.
method Approximate energy surface generation and refinement using Gaussian process regression.
result The number of energy and force evaluations can be reduced by an order of magnitude.

Neural networks' energy landscape is surprisingly flat, suggesting minimal structural changes between minima.

problem Understanding the structure of neural network energy landscapes.
method Constructing continuous paths between minima of recent neural network architectures on CIFAR10 and CIFAR100.
result Paths between minima are essentially flat in both training and test landscapes, implying minimal structural changes.

New methods use machine learning to simulate rare transitions in molecular systems.

problem Simulating rare transitions between metastable states in molecular dynamics.
method Generative models and reinforcement learning for importance sampling.
result Efficiently generated transition paths linking metastable states.

The study examines the behavior of Gaussian processes' minimums and overshoots.

problem Understanding the behavior of Gaussian processes' minimums and overshoots.
method Analyzing conditional distributions and subsequential limits of minimizers.
result The scaled overshoot converges to an exponential random variable with mean σ_*^2.

Improved community detection in heterogeneous SBM with side information.

problem Misclassification in community detection with noisy labels.
method Optimal weighted message passing and minimum energy flow.
result Optimal weighting improves misclassification rate in heterogeneous SBM.

The study finds optimal minimum distances for Green's energy points on compact manifolds.

problem Finding optimal minimum distances for Green's energy points on compact Riemannian manifolds.
method Analyzing point configurations minimizing discrete energy with the Green's function for the Laplacian.
result Every point in a minimizing configuration lies inside a harmonic ball, and the minimum distance has optimal asymptotic order.

In this article we apply a Bochner type formula to show that on a compact conformally flat riemannian manifold (or half-conformally flat in dimension 4) certain types of orthogonal almost-complex structures, if they exist, give the absolute minimum for the energy functional. We give a few examples when such minimizers …

2006-09-18abs ↗pdf ↗

Paper proves existence of minimum energy solutions in 5D contact spin manifolds.

problem Finding minimum energy solutions for CR Yamabe equation in 5D contact spin manifolds.
method Spinorial approach based on a positive mass theorem.
result Existence of minimum energy solutions in 5D contact spin manifolds.

This work develops a generic framework, called the bag-of-paths (BoP), for link and network data analysis. The central idea is to assign a probability distribution on the set of all paths in a network. More precisely, a Gibbs-Boltzmann distribution is defined over a bag of paths in a network, that is, on a representati…

2013-02-27abs ↗pdf ↗

This paper introduces PSI-flatness to better understand ReLU neural networks' flatness and generalization.

problem Existing flatness definitions fail to account for ReLU neural networks' Positively Scale-Invariant (PSI) property.
method Formalizes PSI-flatness on basis path values, proving its relation to generalization.
result Minimums with balanced basis path values are flatter and generalize better.

Study uses Bayes Hilbert framework to recover probability measure flows from sensors.

problem Recovering probability measure flows from moving sensors in a Hilbert space.
method Bayes Hilbert framework, minimum-energy transport, linearization, variational theory.
result Localized sensors can recover reduced path directions but not full state space.

We consider small-time asymptotics for diffusion processes conditioned by their initial and final positions, under the assumption that the diffusivity has a sub-Riemannian structure, not necessarily of constant rank. We show that, if the endpoints are joined by a unique path of minimal energy, and lie outside the sub-R…

2015-05-13abs ↗pdf ↗

Researchers find a surface with minimum bending energy for any genus and isoperimetric ratio.

problem Finding surfaces with minimum bending energy for given genus and isoperimetric ratio.
method Gluing catenoidal bridges to a singular solution of the Willmore equation on a punctured sphere.
result Existence of a surface with minimum bending energy for any genus and isoperimetric ratio.

ECD algorithm speeds up non-convex optimization, offering quantum and stochastic enhancements.

problem Non-convex optimization challenges in machine learning.
method Energy Conserving Descent (ECD) algorithm, stochastic ECD dynamics (sECD), quantum ECD Hamiltonian (qECD).
result ECD and its quantum version achieve exponential speedup over gradient descent.

Study rigidity of Hamiltonians near a minimum in symplectic and magnetic settings.

problem Rigidity of Hamiltonians near a minimum in symplectic and magnetic settings.
method Analyzing Hamiltonian systems near a compact symplectic Morse-Bott minimum, focusing on Zoll flows and magnetic forms.
result A constant curvature quantity characterizes complex space forms among Kähler manifolds.

In this article, we study the small sphere limit of the Wang-Yau quasi-local energy defined in [18,19]. Given a point pp in a spacetime NN, we consider a canonical family of surfaces approaching pp along its future null cone and evaluate the limit of the Wang-Yau quasi-local energy. The evaluation relies on solving …

2015-10-04abs ↗pdf ↗

A physically natural potential energy for simple closed curves in R3\bold R^3 is shown to be invariant under Möbius transformations. This leads to the rapid resolution of several open problems: round circles are precisely the absolute minima for energy; there is a minimum energy threshold below which knotting cannot oc…

1993-01-01abs ↗pdf ↗

Sparse neural networks training is difficult due to optimization failures and energy landscape issues.

problem Training sparse neural networks leads to suboptimal solutions and optimization failures.
method Investigated optimization dynamics and energy landscape in sparse neural networks.
result Sparse neural networks have a linear path with a monotonically decreasing objective from initialization to a good solution, but not from a bad solution.

New index for evaluating cash flow processes over a fixed horizon.

problem Evaluating performance of cash flow processes over a fixed investment horizon.
method Extended acceptability indices to càdlàg processes, providing a new index based on Average Value-at-Risk and running minimum.
result Suggested index represents a RAROC-type model for performance evaluation.

Formula derived for G2G_2-manifolds, showing moduli spaces are incomplete.

problem Incompleteness of moduli spaces for G2G_2-manifolds.
method Derived a formula for the energy of paths in moduli spaces, provided conditions for finite energy and length.
result Compact G2G_2-manifolds produced by the generalised Kummer construction have incomplete moduli spaces.

New algorithm reduces regret in stochastic shortest path problems.

problem Planning and control in environments with unknown dynamics and variable episode lengths.
method Developed an algorithm with a new regret bound of O(BSAK)O(B_\star |S| \sqrt{|A| K}).
result Guaranteed a significant reduction in regret compared to previous methods.

SGD with machine learning noise converges to global minimum exponentially fast.

problem Optimizing machine learning models with stochastic gradient descent.
method Analysis of SGD with machine learning noise, focusing on energy landscapes and gradient noise.
result SGD converges to the global minimum exponentially fast under certain conditions.

We establish a fundamental connection between smooth and polygonal knot energies, showing that the Minimum Distance Energy for polygons inscribed in a smooth knot converges to the Moebius Energy of the smooth knot as the polygons converge to the smooth knot. However, the polygons must converge in a ``nice'' way, and th…

2003-05-29abs ↗pdf ↗

Researchers find optimal configurations of complex knots and links.

problem Finding the most efficient configurations of complex knots and links.
method Minimizing Möbius and Minimum Distance energies by describing them with a small number of free parameters.
result Optimal geometries for Hopf links, Borromean rings, and chain links are found.

New method improves MAP inference for CGMs on path graphs, avoiding approximation and maintaining integrality.

problem Improving MAP inference for aggregated count data in CGMs with small values.
method Formulated as a minimum cost flow problem, solved using DCA with efficient subroutines.
result Outputs higher quality solutions than conventional methods.

The ropelength of a knot is the quotient of its length by its thickness. We consider a family of energy functions for knots, depending on a power p, which approach ropelength as p increases. We describe a numerically computed trefoil knot which seems to be a local minimum for ropelength; there are nearby critical point…

2002-03-20abs ↗pdf ↗

Study shows LLC correlates with neural network compressibility.

problem Evaluating limits of neural network compression.
method Extended minimum description length principle using singular learning theory.
result Complexity estimates based on LLC are linearly correlated with compressibility.

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…

2007-06-19abs ↗pdf ↗

We provide a new proof of a result of X.X.Chen and G.Tian : for a polarized extremal Kähler manifold, an extremal metric attains the minimum of the modified K-energy. The proof uses an idea of C.Li adapted to the extremal metrics using some weighted balanced metrics.

2012-11-23abs ↗pdf ↗

Optimal transport with path constraints for distributions of different masses.

problem Comparing distributions with different total masses under path constraints.
method Introduces a model for unbalanced optimal transport with path constraints, proving existence of solutions.
result Existence of solutions to path constrained unbalanced optimal transport for various constraints.