Exponential family distributions | Continuous distributions
In probability theory, statistics, and machine learning, the continuous Bernoulli distribution is a family of continuous probability distributions parameterized by a single shape parameter , defined on the unit interval , by: The continuous Bernoulli distribution arises in deep learning and computer vision, specifically in the context of variational autoencoders, for modeling the pixel intensities of natural images. As such, it defines a proper probabilistic counterpart for the commonly used binary cross entropy loss, which is often applied to continuous, -valued data. This practice amounts to ignoring the normalizing constant of the continuous Bernoulli distribution, since the binary cross entropy loss only defines a true log-likelihood for discrete, -valued data. The continuous Bernoulli also defines an exponential family of distributions. Writing for the natural parameter, the density can be rewritten in canonical form:. (Wikipedia).
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From playlist Probability Distributions
Bernoulli Distribution Probability & PDF
Examples of finding probabilities with the Bernoulli distribution PDF. Expected value and variance, independence and links to other distributions.
From playlist Probability Distributions
Bernoulli Distribution In Statistics | Bernoulli Distribution Problems and Solutions | Simplilearn
In this Bernoulli Distribution In Statistics tutorial, we will learn Bernoulli distribution and its use. We will also solve a problem related to Bernoulli distribution. In the end, we will see some real-life examples where Bernoulli distribution is used, and we will execute Bernoulli distr
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
Solve a Bernoulli Differential Equation (Part 2)
This video provides an example of how to solve an Bernoulli Differential Equation. The solution is verified graphically. Library: http://mathispower4u.com
From playlist Bernoulli Differential Equations
We use the Binomial Distribution app on ArtofStat.com to visualize the shape of the binomial distribution and to find probabilities for the number of successes in Bernoulli trials.
From playlist Chapter 6: Distributions
B24 Introduction to the Bernoulli Equation
The Bernoulli equation follows from a linear equation in standard form.
From playlist Differential Equations
From playlist Probability Distributions
Continuous Probability Distributions - Basic Introduction
This statistics video tutorial provides a basic introduction into continuous probability distributions. It discusses the normal distribution, uniform distribution, and the exponential distribution. The probability is equal to the area under the curve and the total area under the curve is
From playlist Statistics
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the complete course: http://ocw.mit.edu/6-041F10 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the complete course: http://ocw.mit.edu/6-041F10 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013
Lingfu Zhang (Princeton) -- Anderson-Bernoulli localization near the edge on the 3D lattice
I will talk about localization for the Anderson--Bernoulli model on the 3D lattice. This model is given by the Laplacian plus an i.i.d. Bernoulli potential, and can be used to model an electron hopping inside alloy type materials. Anderson localization of this model was studied by Bourgain
From playlist Northeastern Probability Seminar 2020
Stanford CS229: Machine Learning | Summer 2019 | Lecture 7 - GDA, Naive Bayes & Laplace Smoothing
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3pqcX9P Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
Discrete Distributions: Bernoulli (04a)
Video Lecture from the course INST 414: Advanced Data Science at UMD's iSchool. Full course information here: http://www.umiacs.umd.edu/~jbg/teaching/INST_414/
From playlist Advanced Data Science
Level 1 Chartered Financial Analyst (CFA ®): Common Probability Distributions
Session 2, Reading 10: Probability distributions This video continues a review of quantitative methods in the CFA. This is reading ten. I'm dividing them to two parts, so this is part one and the next video will be part two. In this part one, we'll look at common probability distributions
From playlist Level 1 Chartered Financial Analyst (CFA ®) Volume 1
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018
Stanford CS229: Machine Learning | Summer 2019 | Lecture 6 - Exponential Family & GLM
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Eb7mIi Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
2012 FRM Quantitative Analysis T2.c
This is a sample of our 2012 FRM Quantitative Analysis T2.c video tutorials. View our products here: https://www.bionicturtle.com/products/financial-risk-management/ The Bionic Turtle program is the most effective and affordable preparation aid for the Financial Risk Manager (FRM) exam.
From playlist FRM
Variance of the Bernoulli Distribution | Probability Theory
How do we derive the variance of a Bernoulli random variable? That's what we'll go over in today's probability theory lesson! We'll prove the variance of a Bernoulli random variable with probability of success p is equal to p*(1-p). Remember the variance of a discrete random variable is eq
From playlist Probability Theory