(ML 19.1) Gaussian processes - definition and first examples
Definition of a Gaussian process. Elementary examples of Gaussian processes.
From playlist Machine Learning
(ML 19.2) Existence of Gaussian processes
Statement of the theorem on existence of Gaussian processes, and an explanation of what it is saying.
From playlist Machine Learning
(ML 19.3) Examples of Gaussian processes (part 1)
Illustrative examples of several Gaussian processes, and visualization of samples drawn from these Gaussian processes. (Random planes, Brownian motion, squared exponential GP, Ornstein-Uhlenbeck, a periodic GP, and a symmetric GP).
From playlist Machine Learning
(ML 19.4) Examples of Gaussian processes (part 2)
Illustrative examples of several Gaussian processes, and visualization of samples drawn from these Gaussian processes. (Random planes, Brownian motion, squared exponential GP, Ornstein-Uhlenbeck, a periodic GP, and a symmetric GP).
From playlist Machine Learning
Mixture Models 4: multivariate Gaussians
Full lecture: http://bit.ly/EM-alg We generalise the equations for the case of a multivariate Gaussians. The main difference from the previous video (part 2) is that instead of a scalar variance we now estimate a covariance matrix, using the same posteriors as before.
From playlist Mixture Models
From playlist COMP0168 (2020/21)
(ML 16.6) Gaussian mixture model (Mixture of Gaussians)
Introduction to the mixture of Gaussians, a.k.a. Gaussian mixture model (GMM). This is often used for density estimation and clustering.
From playlist Machine Learning
Machine learning - Introduction to Gaussian processes
Introduction to Gaussian process regression. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at UBC by Nando de Freitas
From playlist Machine Learning 2013
(ML 19.9) GP regression - introduction
Introduction to the application of Gaussian processes to regression. Bayesian linear regression as a special case of GP regression.
From playlist Machine Learning
DSI | MuyGPs: Scalable Gaussian Process Hyperparameter Estimation Using Local Cross-Validation
The utilization of large and complex data by machine learning in support of decision-making is of increasing importance in many scientific and national security domains. However, the need for uncertainty estimates or similar confidence indicators inhibits the integration of many popular ma
From playlist DSI Virtual Seminar Series
Integrating MATLAB and C, Part 2 Visualizing and Testing CC++ Code
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 For more on MATLAB and C/C++, visit: https://www.mathworks.com/programs/resource-portals/matlab-coder/index.html
From playlist Integrating MATLAB and C/C++
Thirteenth Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk
Date: Wednesday, February 10, 2021, 10:00am EDT Speaker: Hui Ji, National University of Singapore Title: Self-supervised Deep Learning for Image Recovery Abstract: In recent years, deep learning emerges as one promising technique for solving many ill-posed inverse problems in image rec
From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series
Raspberry Pi 3 Tutorial For Beginners | Raspberry Pi 3 Projects Explained | Edureka | IoT Live - 3
🔥Edureka IoT Certification Training - https://www.edureka.co/iot-certification-training This "Raspberry Pi 3 Tutorial" video by Edureka will help you in getting started with Raspberry Pi 3 with examples. 🔴Subscribe to our channel to get video updates. Hit the subscribe button above: ht
From playlist Edureka Live Classes 2020
Juan Luis Vázquez: The theory of nonlinear diffusion with fractional operators
Abstract: In this talk I will report on some of the progress made by the author and collaborators on the topic of nonlinear diffusion equations involving long distance interactions in the form of fractional Laplacian operators. The nonlinearities are of the following types: porous medium,
From playlist Partial Differential Equations
Statistical Rethinking Fall 2017 - week08 lecture15
Week 08, lecture 15 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 12. Slides are available here: https://speakerdeck.com/rmcelreath/statistical-rethinking-fall-2017-lecture-15 Additional informatio
From playlist Statistical Rethinking Fall 2017
Black Hat USA 2010: Exploiting Timing Attacks in Widespread Systems 1/5
Speakers: Nate Lawson, Taylor Nelson Much has been written about timing attacks since they first appeared over 15 years ago. However, many developers still believe that they are only theoretically exploitable and don't make it a priority to fix them. We have notified vendors who declined
From playlist BH USA 2010 - NETWORK
Automating Machine Learning | Data Science Institute
ABOUT THE TALK: Recent years have seen a widespread adoption of machine learning in industry and academia, impacting diverse areas from advertisement to personal medicine. As more and more areas adopt machine learning and data science techniques, the question arises on how much expertise
From playlist talks
Raspberry Pi 3 Tutorial | Raspberry Pi 3 Projects | IoT Projects | IoT Tutorial | Edureka
( IoT Certification Training : https://www.edureka.co/iot-certification-training ) This "Raspberry Pi 3 Tutorial" video by Edureka will help you in getting started with Raspberry Pi 3. This Raspberry Pi Tutorial video helps you to learn the following topics: 1. What is Raspberry Pi? 2.
From playlist Internet of Things - IoT Tutorial for Beginners | Edureka
Machine learning - Gaussian processes
Regression with Gaussian processes Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at UBC by Nando de Freitas
From playlist Machine Learning 2013
Replication or Exploration? Sequential Design for Stochastic Simulation Experiments
The Data Science Institute (DSI) hosted a virtual seminar by Robert Gramacy from Virginia Tech on March 15, 2021. Read more about the DSI seminar series at https://data-science.llnl.gov/latest/seminar-series. We investigate the merits of replication and provide methods that search for opti
From playlist DSI Virtual Seminar Series