arXiv research

NN-Turb generates turbulent velocity statistics using neural networks.

SAGE generates subsurface velocity models from sparse well logs and seismic images.

We have studied the statistical mechanics of money circulation in a closed economic system. An explicit statistical formulation of the circulation velocity of money is presented for the first time by introducing the concept of holding time of money. The result indicates that the velocity is governed by behavior pattern…

New method estimates velocity fields for minimizing $f$-divergences without overfitting.

LFIS uses a time-dependent velocity field to sample from complex distributions.

Paper introduces EnDKF for more accurate pose tracking.

Bitcoin's monetary velocity is constrained by network friction, leading to significant utility contraction during shocks.

The understanding of the dynamics of the velocity gradients in turbulent flows is critical to understanding various non-linear turbulent processes. The pressure-Hessian and the viscous-Laplacian govern the evolution of the velocity-gradients and are known to be non-local in nature. Over the years, several simplified dy…

This work analyzes the statistical properties of neural ODEs for distribution learning.

Optimizes angular velocity transfers for rigid bodies under deadline constraints.

GPMI method interpolates uncertain atrial conduction velocity on non-Euclidean manifolds.

Flow matching KL divergence bound derived for smooth distributions.

MeanFlow training is unstable due to misusing conditional velocity, leading to variance issues.

Flow matching adapts to manifold structures without diffusion.

DFM models are analyzed for generating distributions with provable convergence.

We discuss some aspects about the computation of kinematic, spectroscopic, Fermi and astrometric relative velocities that are geometrically defined in general relativity. Mainly, we state that kinematic and spectroscopic relative velocities only depend on the 4-velocities of the observer and the test particle, unlike F…

DSNE visualizes data velocity in lower dimensions.

Develops a method for non-equilibrium importance sampling to estimate expectations and constants.

RFM improves CNFs by adding a boundary constraint term and matching velocity fields.

Log-ergodic model improves velocity of money prediction.

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes (RANS) equations combined with the turbulence model are applied to solve incompr…

Optimal self-distillation improves generative models' velocity risk and mode recovery.

Bayesian geoacoustic inversion improved using MDN.

We prove that, in a space-time of dimension n>3 with a velocity field that is shear-free, vorticity-free and acceleration-free, the covariant divergence of the Weyl tensor is zero if the contraction of the Weyl tensor with the velocity is zero. The other way, if the covariant divergence of the Weyl tensor is zero, then…

Proves strong solutions for graphical Brakke flows with $L^2$ normal velocity.

CCVFM uses coreset to improve generative models by refining residual flows.

New method distinguishes cause from effect using causal velocity.

The determinants of the velocity of money have been examined based on life-cycle hypothesis. The velocity of money can be expressed by reciprocal of the average value of holding time which is defined as interval between participating exchanges for one unit of money. This expression indicates that the velocity is govern…

A conservative drifting method improves generative modeling by using KDE gradients, proving convergence rates.

A new method interprets astrophysical spectra using geometric paths to distinguish line profiles.

Neural solver computes Wasserstein geodesics and velocity fields efficiently.

Develops scalable model for learning velocity fields in complex traffic scenarios.

Generative sampler learns velocity fields for efficient posterior inference.

Formulates mechanics for probability distributions on statistical manifold.

In this communication, complex systems with a near trivial dynamics are addressed. First, under the hypothesis of equiprobability in the asymptotic equilibrium, it is shown that the (hyper) planar geometry of an $N$-dimensional multi-agent economic system implies the exponential (Boltzmann-Gibss) wealth distribution an…

Time dilation $\frac{1}{\sqrt{1-v^2}}$ and relative velocity $v$ are observationally indistinguishable in the special theory of relativity, a duality that carries over into the general theory under Fermi coordinates along a curve (in coordinate-independent language, in the tangent Minkowski space along the curve). For …

An $(r,n)$-velocity is an $r$-jet with source at $0 \in \R^n$, and target in a manifold $Y$. An $(r,n)$-velocity is said to be regular, if it has a representative which is an immersion at $0 \in \R^{n}$. The manifold $T^{r}_{n}Y$ of $(r,n)$-velocities as well as its open, $L^{r}_{n}$-invariant, dense submanifold $\Imm …

We have studied numerically the statistical mechanics of the dynamic phenomena, including money circulation and economic mobility, in some transfer models. The models on which our investigations were performed are the basic model proposed by A. Dragulescu and V. Yakovenko [1], the model with uniform saving rate develop…

Study uses neural networks to predict wall quantities in turbulent flows.

In this study, the concept of dual Lorentzian homotetic exponential motions in is discussed and their velocities, accelerations obtained. Also, some geometric results between velocity and acceleration vectors of a point in a spatial motion are obtained. Finally, the theorems related to acceleration and acceleration cen…

The paper develops a new class of financial market models. These models are based on generalized telegraph processes: Markov random flows with alternating velocities and jumps occurring when the velocities are switching. While such markets may admit an arbitrage opportunity, the model under consideration is arbitrage-f…

Neural net reconstructs dark matter density from halo velocities.

We introduce a measure for estimating the best risk-return relation of power production in wind farms within a given time-lag, conditioned to the velocity field. The velocity field is represented by a scalar that weighs the influence of the velocity at each wind turbine at present and previous time-steps for the presen…

Diffusion models struggle in high dimensions due to objective function degradation.

In this paper the dependence of wealth distribution and the velocity of money on the required reserve ratio is examined based on a random transfer model of money and computer simulations. A fractional reserve banking system is introduced to the model where money creation can be achieved by bank loans and the monetary a…

Clarifies method of phase synchronization for decoupling linear differential equations.

Anomalous diffusion in SGD reveals interactions between hyperparameters and Hessian.

TVM improves generative modeling by matching terminal velocities.