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Langevin Monte Carlo (LMC) is an iterative algorithm used to generate samples from a distribution that is known only up to a normalizing constant. The nonasymptotic dependence of its mixing time on the dimension and target accuracy is…

Machine Learning · Statistics 2020-02-26 Niladri S. Chatterji , Jelena Diakonikolas , Michael I. Jordan , Peter L. Bartlett

Non-convex sampling is a key challenge in machine learning, central to non-convex optimization in deep learning as well as to approximate probabilistic inference. Despite its significance, theoretically there remain many important…

Machine Learning · Computer Science 2024-09-18 Mohammad Reza Karimi , Ya-Ping Hsieh , Andreas Krause

In the context of preserving stationary states, e.g. lake at rest and moving equilibria, a new formulation of the shallow water system, called Flux Globalization has been introduced by Cheng et al. (2019). This approach consists in…

Numerical Analysis · Mathematics 2023-11-09 Mirco Ciallella , Davide Torlo , Mario Ricchiuto

The Mean Field Variational Bayes (MFVB) method is one of the most computationally efficient techniques for Bayesian inference. However, its use has been restricted to models with conjugate priors or those that require analytical…

Computation · Statistics 2023-05-18 Minh-Ngoc Tran , Paco Tseng , Robert Kohn

This paper proposes an approach combining the Volume Penalization (VP) and the the Lattice Boltzmann method (LBM) to compute fluid structure interaction involving rigid bodies. The method consists in adding a force term in the LBM…

Computational Physics · Physics 2021-06-11 Erwan Liberge , Claudine Béghein

In this paper, an efficient fragile blind quad watermarking scheme for image tamper detection and recovery based on lifting wavelet transform and genetic algorithm is proposed. TRLG generates four compact digests with super quality based on…

Cryptography and Security · Computer Science 2018-03-09 Behrouz Bolourian Haghighi , Amir Hossein Taherinia , Amir Hossein Mohajerzadeh

We present a multilevel Monte Carlo (MLMC) method for the uncertainty quantification of variably saturated porous media flow that are modeled using the Richards' equation. We propose a stochastic extension for the empirical models that are…

Numerical Analysis · Mathematics 2019-03-22 Prashant Kumar , Carmen Rodrigo , Francisco J. Gaspar , Cornelis W. Oosterlee

In numerical simulations of complex fluid dynamical problems, unphysical negative density or pressure may appear, causing blow-up of the computation. With the aim of obtaining positivity-preserving solutions with multi-scale resolution for…

Computational Physics · Physics 2025-01-06 Zhen-Hua Jiang , Xi Deng , Lin-Tao Huang , Chao Yan , Feng Xiao , Jian Yu

In scalar turbulence it is sometimes the case that the scalar diffusivity is smaller than the viscous diffusivity. The thermally-driven turbulent convection in water is a typical example. In such a case the smallest scale in the problem is…

Fluid Dynamics · Physics 2018-10-17 Kai Leong Chong , Guangyu Ding , Ke-Qing Xia

Solving the quantum many-body Schr\"odinger equation is a fundamental and challenging problem in the fields of quantum physics, quantum chemistry, and material sciences. One of the common computational approaches to this problem is Quantum…

Computational Physics · Physics 2023-11-03 Kirill Neklyudov , Jannes Nys , Luca Thiede , Juan Carrasquilla , Qiang Liu , Max Welling , Alireza Makhzani

In the traditional load flow analysis, a key assumption is that the input variables, i.e., generator output and customer demand, are fixed in time and the associated response has no variability. This assumption, however, is no longer valid…

Signal Processing · Electrical Eng. & Systems 2021-01-20 Brandon Johnson , Nathan L. Gibson , Eduardo Cotilla-Sanchez

We introduce Tempered Geodesic Markov Chain Monte Carlo (TG-MCMC) algorithm for initializing pose graph optimization problems, arising in various scenarios such as SFM (structure from motion) or SLAM (simultaneous localization and mapping).…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Tolga Birdal , Umut Şimşekli , M. Onur Eken , Slobodan Ilic

In this work we study the convergence properties of the one-level parallel Schwarz method with Robin transmission conditions applied to the one-dimensional and two-dimensional Helmholtz and Maxwell's equations. One-level methods are not…

Numerical Analysis · Mathematics 2022-01-13 Niall Bootland , Victorita Dolean , Alexandros Kyriakis , Jennifer Pestana

In this paper, a novel weighted nonlocal total variation (WNTV) method is proposed. Compared to the classical nonlocal total variation methods, our method modifies the energy functional to introduce a weight to balance between the labeled…

Computer Vision and Pattern Recognition · Computer Science 2018-02-01 Haohan Li , Zuoqiang Shi , Xiaoping Wang

We develop and implement a novel lattice Boltzmann scheme to study multicomponent flows on curved surfaces, coupling the continuity and Navier-Stokes equations with the Cahn-Hilliard equation to track the evolution of the binary fluid…

Computational Physics · Physics 2019-12-25 Victor E. Ambruş , Sergiu Busuioc , Alexander J. Wagner , Fabien Paillusson , Halim Kusumaatmaja

The diffusion models (DMs) have demonstrated the remarkable capability of generating images via learning the noised score function of data distribution. Current DM sampling techniques typically rely on first-order Langevin dynamics at each…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Fangyikang Wang , Hubery Yin , Lei Qian , Yinan Li , Shaobin Zhuang , Huminhao Zhu , Yilin Zhang , Yanlong Tang , Chao Zhang , Hanbin Zhao , Hui Qian , Chen Li

In this paper, we propose a hybrid lattice Boltzmann method (HLBM) for solving fluid-structure interaction problems. The proposed numerical approach is applied to model the flow induced by a vibrating thin lamina submerged in a viscous…

Computational Physics · Physics 2020-06-25 Giovanni Di Ilio , Daniele Chiappini , Stefano Ubertini , Gino Bella , Sauro Succi

We consider the constrained sampling problem where the goal is to sample from a target distribution on a constrained domain. We propose skew-reflected non-reversible Langevin dynamics (SRNLD), a continuous-time stochastic differential…

Machine Learning · Computer Science 2025-04-16 Hengrong Du , Qi Feng , Changwei Tu , Xiaoyu Wang , Lingjiong Zhu

In this article, a coupled Two-relaxation-time Lattice Boltzmann-Volume penalization (TRT-LBM-VP) method is presented to simulate flows past obstacles. Two relaxation times are used in the collision operator, of which one is related to the…

Computational Physics · Physics 2021-03-30 Xiongwei Cui , Zhikai Wang , Xiongliang Yao , Minghao Liu , Fulin Yu

The Landweber algorithm defined on complex/real Hilbert spaces is a gradient descent algorithm for linear inverse problems. Our contribution is to present a novel method for accelerating convergence of the Landweber algorithm. In this…

Information Theory · Computer Science 2020-01-20 Tadashi Wadayama , Satoshi Takabe