Lattice Boltzmann methods

Lecture 12A : The Boltzmann Machine learning algorithm

Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] Lecture 12A : The Boltzmann Machine learning algorithm

From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]

Lecture 12.1 — Boltzmann machine learning — [ Deep Learning | Geoffrey Hinton | UofT ]

From playlist Neural Networks for Machine Learning — Geoffrey Hinton, UofT [FULL COURSE]

A. Eberle: Couplings & converg. to equilibrium f. Langevin dyn. & Hamiltonian Monte Carlo methods

The lecture was held within the framework of the Hausdorff Trimester Program: Kinetic Theory Abstract: Coupling methods provide a powerful approach to quantify convergence to equilibrium of Markov processes in appropriately chosen Wasserstein distances. This talk will give an overview on

From playlist Workshop: Probabilistic and variational methods in kinetic theory

Modelling multicomponent fluid flows with the lattice Boltzmann method

Halim Kusumaatmaja Durham University, UK

From playlist 2018 Modeling and Simulation of Interface Dynamics in Fluids/Solids and Their Applications

John HILLER - Nonperturbative light-front methods

https://indico.math.cnrs.fr/event/2435/

From playlist Workshop “Hamiltonian methods in strongly coupled Quantum Field Theory”

Neural networks [5.8] : Restricted Boltzmann machine - extensions

From playlist Neural networks class - Université de Sherbrooke

Joan ELIAS MIRÓ - Precise calculations with the Renormalized Hamiltonian Truncation approach

https://indico.math.cnrs.fr/event/2435/

From playlist Workshop “Hamiltonian methods in strongly coupled Quantum Field Theory”

Dana Randall: Sampling algorithms and phase transitions

Markov chain Monte Carlo methods have become ubiquitous across science and engineering to model dynamics and explore large combinatorial sets. Over the last 20 years there have been tremendous advances in the design and analysis of efficient sampling algorithms for this purpose. One of the

From playlist Probability and Statistics

Talk Jingwei Hu: Deterministic solution of the Boltzmann equation Fast spectral methods

The lecture was held within the of the Hausdorff Trimester Program: Kinetic Theory Abstract: The Boltzmann equation, an integro-differential equation for the molecular distribution function in the physical and velocity phase space, governs the fluid flow behavior at a wide range of physi

From playlist Summer School: Trails in kinetic theory: foundational aspects and numerical methods

MLDS 2020 - 3 Boltzmann Generators

From playlist MLDS

Lec 19 | MIT 3.320 Atomistic Computer Modeling of Materials

Free Energies and Physical Coarse-Graining View the complete course at: http://ocw.mit.edu/3-320S05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 3.320 Atomistic Computer Modeling of Materials

01 - LATTICE BOLTZMANN METHOD - INTRODUCTION - LEGENDADO: PT-BR

Hello guys, this is my first video of this course, I hope that this may be helpful for other people that are trying to learn the basics of the Lattice Boltzmann Method. Please comments and suggestions are always welcome, so feel yourself comfortable. My Git Hub Blog: https://brunomagach

From playlist Summer of Math Exposition Youtube Videos

Lecture 11E : How a Boltzmann Machine models data

Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] Lecture 11E : How a Boltzmann Machine models data

From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]

P. Di Francesco: "Triangular Ice Combinatorics"

Asymptotic Algebraic Combinatorics 2020 "Triangular Ice Combinatorics" P. Di Francesco - University of Illinois & IPhT Saclay Abstract: Alternating Sign Matrices (ASM) are at the confluent of many interesting combinatorial/algebraic problems: Laurent phenomenon for the octahedron equatio

From playlist Asymptotic Algebraic Combinatorics 2020

Lec 17 | MIT 3.320 Atomistic Computer Modeling of Materials

Monte Carlo Simulations: Application to Lattice Models, Sampling Errors, Metastability View the complete course at: http://ocw.mit.edu/3-320S05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 3.320 Atomistic Computer Modeling of Materials

Tensor Network Methods in Four Dimensional Field Theory by Daisuke Kadoh

PROGRAM Nonperturbative and Numerical Approaches to Quantum Gravity, String Theory and Holography (ONLINE) ORGANIZERS: David Berenstein (UCSB), Simon Catterall (Syracuse University), Masanori Hanada (University of Surrey), Anosh Joseph (IISER, Mohali), Jun Nishimura (KEK Japan), David Sc

From playlist Nonperturbative and Numerical Approaches to Quantum Gravity, String Theory and Holography (Online)

Lecture Marie Therese Wolfram: On Boltzmann type equations in socio economic applications

The lecture was held within the of the Hausdorff Junior Trimester Program: Kinetic Theory Abstract: In this talk we discuss how kinetic or so-called Boltzmann type models can be used to describe the dynamics of large interacting agents systems. We focus on two applications – a continuous

From playlist Summer School: Trails in kinetic theory: foundational aspects and numerical methods

Marco Bernardi - Quantum mechanical calculations of electron interactions in condensed matter

Recorded 12 April 2022. Marco Bernardi of the California Institute of Technology presents "Precise quantum mechanical calculations of electron interactions and dynamics in condensed matter" at IPAM's Model Reduction in Quantum Mechanics Workshop. Learn more online at: http://www.ipam.ucla.

From playlist 2022 Model Reduction in Quantum Mechanics Workshop

Why Your Pee Looks Like A Chain

The first 100 people to go to https://blinkist.com/stevemould will get unlimited access for 1 week to try it out. You'll also get 25% off if you want full membership. Have you noticed the shape of your urine stream when you pee? It does this twisty undulating thing. But why? And why do th

From playlist Chemistry

PDE FIND

We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity promoting techniques to select the nonlinear and partial derivative

From playlist Research Abstracts from Brunton Lab