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The exponential contraction in $L^1$-Wasserstein distance and exponential convergence in $L^q$-Wasserstein distance ($q\geq 1$) are considered for stochastic differential equations with irregular drift. When the irregular drift drift is…

Probability · Mathematics 2024-04-22 Shao-Qin Zhang

We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that…

Probability · Mathematics 2015-08-04 David Baños , Paul Krühner

In this paper we derive explicit formulas of the R\'enyi information, Shannon entropy and Song measure for the invariant density of one dimensional ergodic diffusion processes. In particular, the diffusion models considered include the…

Probability · Mathematics 2007-11-13 Alessandro De Gregorio , Stefano Iacus

Estimates of densities of convolution semigroups of probability measures are given under specific assumptions on the corresponding L\'evy measure and the L\'evy--Khinchin exponent. The assumptions are satisfied, e.g., by tempered stable…

Probability · Mathematics 2008-04-02 Paweł Sztonyk

The Renyi entropy is a generalisation of the Shannon entropy that is sensitive to the fine details of a probability distribution. We present results for the Renyi entropy of the totally asymmetric exclusion process (TASEP). We calculate…

Statistical Mechanics · Physics 2017-11-10 Anthony J. Wood , Richard A. Blythe , Martin R. Evans

Let $X=(X_t)_{t\geq 0}$ be a known process and $T$ an unknown random time independent of $X$. Our goal is to derive the distribution of $T$ based on an iid sample of $X_T$. Belomestny and Schoenmakers (2015) propose a solution based the…

Probability · Mathematics 2019-05-27 Viktor Schulmann

We revisit the problem of the estimation of the differential entropy $H(f)$ of a random vector $X$ in $R^d$ with density $f$, assuming that $H(f)$ exists and is finite. In this note, we study the consistency of the popular nearest neighbor…

Statistics Theory · Mathematics 2021-02-26 Luc Devroye , László Györfi

We study the problem of the non-parametric estimation for the density $\pi$ of the stationary distribution of a stochastic two-dimensional damping Hamiltonian system $(Z_t)_{t\in[0,T]}=(X_t,Y_t)_{t \in [0,T]}$. From the continuous…

Statistics Theory · Mathematics 2020-01-29 Sylvain Delattre , Arnaud Gloter , Nakahiro Yoshida

Applying Zvonkin's transform, the exponential convergence in Wasserstein distance for a class of functional SDEs with H\"older continuous drift is obtained. This combining with log-Harnack inequality implies the same convergence in the…

Probability · Mathematics 2018-11-06 Xing Huang

Consider the following distribution dependent SDE: $$ {\mathrm d} X_t=\sigma_t(X_t,\mu_{X_t}){\mathrm d} W_t+b_t(X_t,\mu_{X_t}){\mathrm d} t, $$ where $\mu_{X_t}$ stands for the distribution of $X_t$. In this paper for non-degenerate…

Probability · Mathematics 2019-10-30 Michael Röckner , Xicheng Zhang

We present novel bounds for estimating discrete probability distributions under the $\ell_\infty$ norm. These are nearly optimal in various precise senses, including a kind of instance-optimality. Our data-dependent convergence guarantees…

Statistics Theory · Mathematics 2024-02-14 Aryeh Kontorovich , Amichai Painsky

We consider the problem of approximating the empirical Shannon entropy of a high-frequency data stream under the relaxed strict-turnstile model, when space limitations make exact computation infeasible. An equivalent measure of entropy is…

Computation · Statistics 2013-04-18 Peter Clifford , Ioana Ada Cosma

Discrete diffusion models have emerged as a powerful paradigm for generative modeling on sequence data; however, the information-theoretic principles governing their reverse processes remain significantly less understood than those of their…

Machine Learning · Computer Science 2026-02-10 Alberto Foresti , Mustapha Bounoua , Giulio Franzese , Luca Ambrogioni , Pietro Michiardi

We consider distributions of ordered random vectors with given one-dimensional marginal distributions. We give an elementary necessary and sufficient condition for the existence of such a distribution with finite entropy. In this case, we…

Statistics Theory · Mathematics 2015-09-08 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

The weak law of large numbers implies that, under mild assumptions on the source, the Renyi entropy per produced symbol converges (in probability) towards the Shannon entropy rate. This paper quantifies the speed of this convergence for…

Information Theory · Computer Science 2017-05-01 Maciej Skorski

We describe a quantum algorithm to estimate the $\alpha$-Renyi entropy of an unknown density matrix $\rho\in\mathcal{C}^{d\times d}$ for $\alpha\neq 1$ by combining the recent technique of quantum singular value transformations with the…

Quantum Physics · Physics 2021-09-01 Sathyawageeswar Subramanian , Min-Hsiu Hsieh

As two crucial tools characterizing regularity properties of stochastic systems, the log-Harnack inequality and Bismut formula have been intensively studied for distribution dependent (McKean-Vlasov) SDEs. However, due to technical…

Probability · Mathematics 2023-07-10 Xing Huang , Feng-Yu Wang

In this paper, the well-posedness for one-dimensional path dependent McKean-Vlasov SDEs with $\alpha$($\alpha\geq \frac{1}{2}$)-H\"{o}lder continuous diffusion is investigated. Moreover, the associated quantitative propagation of chaos in…

Probability · Mathematics 2022-09-20 Xing Huang , Xucheng Wang

Observing how long a dynamical system takes to return to some state is one of the most simple ways to model and quantify its dynamics from data series. This work proposes two formulas to estimate the KS entropy and a lower bound of it, a…

Chaotic Dynamics · Physics 2015-05-14 M. S. Baptista , E. J. Ngamga , Paulo R. F. Pinto , Margarida Brito , J. Kurths

Given an i.i.d. sample from a distribution $F$ on $\mathbb{R}$ with uniformly continuous density $p_0$, purely data-driven estimators are constructed that efficiently estimate $F$ in sup-norm loss and simultaneously estimate $p_0$ at the…

Statistics Theory · Mathematics 2011-01-10 Evarist Giné , Richard Nickl