Artificial neural networks

Helmholtz machine

The Helmholtz machine (named after Hermann von Helmholtz and his concept of Helmholtz free energy) is a type of artificial neural network that can account for the hidden structure of a set of data by being trained to create a generative model of the original set of data. The hope is that by learning economical representations of the data, the underlying structure of the generative model should reasonably approximate the hidden structure of the data set. A Helmholtz machine contains two networks, a bottom-up recognition network that takes the data as input and produces a distribution over hidden variables, and a top-down "generative" network that generates values of the hidden variables and the data itself. At the time, Helmholtz machines were one of a handful of learning architectures that used feedback as well as feedforward to ensure quality of learned models. Helmholtz machines are usually trained using an unsupervised learning algorithm, such as the wake-sleep algorithm. They are a precursor to variational autoencoders, which are instead trained using backpropagation. Helmholtz machines may also be used in applications requiring a supervised learning algorithm (e.g. character recognition, or position-invariant recognition of an object within a field). (Wikipedia).

Video thumbnail

The Mandelbrot set is a churning machine

Its job is to fling off the red pixels and hang onto the green ones. Audio by @Dorfmandesign

From playlist mandelstir

Video thumbnail

Amazing railway track laying machine

I want one of these.

From playlist Science

Video thumbnail

Stirring the Mandelbrot Set: a checkerboard

http://code.google.com/p/mandelstir/

From playlist mandelstir

Video thumbnail

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]

Video thumbnail

Physics 23.5 (Chemistry) Thermodynamic Potentials (4 of TBD) What is Helmholtz Free Energy?

Visit http://ilectureonline.com for more math and science lectures! http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn about the 3rd of the 4 thermodynamic potentials: the Helmholtz free energy is F=U-TS or A=U-TS. Previous video in this ser

From playlist CHEMISTRY 9.5 THERMODYNAMICS POTENTIALS

Video thumbnail

Stirring the Mandelbrot Set

http://code.google.com/p/mandelstir/

From playlist mandelstir

Video thumbnail

Simple Machines (4 of 7) Pulleys; Calculating the Amount of Work Done

For the pulley simple machine shows how to calculate the amount of work done when raising an object and why simple machines do not make your work easier! A simple machine is a mechanical device that changes the direction and the magnitude of a force. In general, they can be defined as th

From playlist Mechanics

Video thumbnail

the ljungstroms radial steam turbine

Here is an animation of Ljungstroms steam turbine

From playlist Turbines

Video thumbnail

Lecture 8: Shading, Special Cases, Lunar Surface, Scanning Electron Microscope, Green's Theorem

MIT 6.801 Machine Vision, Fall 2020 Instructor: Berthold Horn View the complete course: https://ocw.mit.edu/6-801F20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63pfpS1gV5P9tDxxL_e4W8O In this lecture, we explore Hapke surfaces and how they compare to Lambertian sur

From playlist MIT 6.801 Machine Vision, Fall 2020

Video thumbnail

Nordenfelt 2-barrel Anti-Torpedo-Boat gun

Animation of a 2-barrel Nordenfelt 1 inch anti-torpedo boat gun, circa 1885. Nordenfelt's first mechanism, as used in the 4-barrel gun, was rather cumbersome. This second system was much more compact, and was used on other models, including 5-barrel rifle calibre guns.The 2-barrel gun was

From playlist Hand powered machine guns

Video thumbnail

21st Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk

Date: Wednesday, April 14, 2021, 10:00am Eastern Time Zone (US & Canada) Speaker: Fioralba Cakoni, Rutgers University Title: On some old and new spectral problems in inverse scattering theory Abstract: Scattering poles, non-scattering frequencies and transmission eigenvalues are intrins

From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series

Video thumbnail

Open questions in turbulent stratified mixing:Do we even know what we do not know? by C.P. Caulfield

ABSTRACT: Understanding how turbulence leads to the enhanced irreversible transport of heat and other scalars (such as salt and pollutants) in density-stratified fluids is a fundamental and central problem in geophysical and environmental fluid dynamics. There is a wide range of highly im

From playlist ICTS Colloquia

Video thumbnail

20 AWESOME Electromagnetic induction in laboratory!!!

This videos shoe and describes about the Electromagnetic Induction, Faraday's observation.It also describes about the magnitude and direction of induced e.m.f, Faraday’s Laws of Electromagnetic Induction and the Lenz’s Law.

From playlist ELECTROMAGNETISM

Video thumbnail

Kelvin-Helmholtz Instability - Sixty Symbols

Additional video on how the experiment works at: https://youtu.be/mf_143gkKSQ More links and info below ↓ ↓ ↓ This video features Professor Mike Merrifield from the University of Nottingham. Stripey Clouds: https://youtu.be/rOdRbUQzajo Cloud video on Objectivity: https://youtu.be/C6Fws5

From playlist Weather Videos with Mike - Sixty Symbols

Video thumbnail

Lecture 7: Gradient Space, Reflectance Map, Image Irradiance Equation, Gnomonic Projection

MIT 6.801 Machine Vision, Fall 2020 Instructor: Berthold Horn View the complete course: https://ocw.mit.edu/6-801F20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63pfpS1gV5P9tDxxL_e4W8O This lecture discusses the photometric stereo problem, estimating motion graphica

From playlist MIT 6.801 Machine Vision, Fall 2020

Video thumbnail

Live CEOing Ep 362: PDE Modeling in Wolfram Language

In this episode of Live CEOing, Stephen Wolfram discusses PDE modeling for the Wolfram Language. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram here: https://www.tw

From playlist Behind the Scenes in Real-Life Software Design

Video thumbnail

Why Blowing in Bottles Makes Sound and Helmholtz Resonance

An explanation of why blowing in a bottle makes a sound, basically explaining how Helmholtz resonance works and how to bottles are Helmholtz resonators. The same explanation works for what role the speaker plays in moving objects/bottles using sound, the acoustic propulsion in one of my ot

From playlist Science Projects

Video thumbnail

Statistical Mechanics (Tutorial) by Chandan Dasgupta

Statistical Physics Methods in Machine Learning DATE: 26 December 2017 to 30 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "t

From playlist Statistical Physics Methods in Machine Learning

Video thumbnail

Helmholtz Resonator - Think you know how helmholtz resonators work?

Helmholtz Resonator - Here's a gentle physics lesson on helmholtz resonators, complete with multiple demonstrations. Dr. Andres Larraza of the naval postgraduate school demonstrates various helholtz resonators to the 2015 Monterey Academy of Oceanographic Science: MAOS helmholtz resonat

From playlist In-class Physics Demonstrations

Video thumbnail

Simple Machines (1 of 7) Pulleys; Defining Forces, Distances and MA

For the pulley simple machine this video defines the terms input and output force, input and output distance and mechanical advantage. A simple machine is a mechanical device that changes the direction and the magnitude of a force. In general, they can be defined as the simplest mechanis

From playlist Mechanics

Related pages

Restricted Boltzmann machine | Autoencoder | Boltzmann machine | Backpropagation | Wake-sleep algorithm | Generative model | Hopfield network | Artificial neural network