Normal distribution | Probability distributions
In probability theory, the rectified Gaussian distribution is a modification of the Gaussian distribution when its negative elements are reset to 0 (analogous to an electronic rectifier). It is essentially a mixture of a discrete distribution (constant 0) and a continuous distribution (a truncated Gaussian distribution with interval ) as a result of censoring. (Wikipedia).
Sequences: Introduction to Solving Recurrence Relations
This video introduces solving recurrence relations by the methods of inspection, telescoping, and characteristic root technique. mathispower4u.com
From playlist Sequences (Discrete Math)
Applying the recursive formula to a sequence to determine the first five terms
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Applying the recursive formula to a geometric sequence
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Determining the first five terms of a geometric recursive formula
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Stéphane Mallat - Multiscale Models for Image Classification and Physics with Deep Networks
Abstract: Approximating high-dimensional functionals with low-dimensional models is a central issue of machine learning, image processing, physics and mathematics. Deep convolutional networks are able to approximate such functionals over a wide range of applications. This talk shows that t
From playlist 2nd workshop Nokia-IHES / AI: what's next?
Evaluating Recurrence Relations (1 of 4: When do you apply Recurrence Relations?)
More resources available at www.misterwootube.com
From playlist Further Integration
Geoffrey Hinton: "Using Backpropagation for Fine-Tuning a Generative Model..."
Graduate Summer School 2012: Deep Learning, Feature Learning "Part 2: Using Backpropagation for Fine-Tuning a Generative Model to be Better at Discrimination" Geoffrey Hinton, University of Toronto Institute for Pure and Applied Mathematics, UCLA July 9, 2012 For more information: https
From playlist GSS2012: Deep Learning, Feature Learning
How to find a geometric rule for a recursive sequence
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Giovanni Peccati: Cancellations in random nodal sets
Abstract: I will discuss second order results for the length of nodal sets and the number of phase singularities associated with Gaussian random Laplace eigenfunctions, both on compact manifolds (the flat torus) and on subset of the plane. I will mainly focus on 'cancellation phenomena' fo
From playlist Probability and Statistics
How to use the recursive formula to evaluate the first five terms
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Lecture 14/16 : Deep neural nets with generative pre-training
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 14A Learning layers of features by stacking RBMs 14B Discriminative fine-tuning for DBNs 14C What happens during discriminative fine-tuning? 14D Modeling real-valued data with an RBM 14E RBMs are Infinite Sigmoid Beli
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
What is the recursive formula and how do we use it
👉 Learn about sequences. A sequence is a list of numbers/values exhibiting a defined pattern. A number/value in a sequence is called a term of the sequence. There are many types of sequence, among which are: arithmetic and geometric sequence. An arithmetic sequence is a sequence in which
From playlist Sequences
Using the recursive formula to find the first four terms of a sequence
👉 Learn all about recursive sequences. Recursive form is a way of expressing sequences apart from the explicit form. In the recursive form of defining sequences, each term of a sequence is expressed in terms of the preceding term unlike in the explicit form where each term is expressed in
From playlist Sequences
Machine Learning Summer School 2014 in Pittsburgh http://www.mlss2014.com See the website for more videos and slides. Nando de Freitas Lecture 3
From playlist Talks and tutorials
CS231n Lecture 5 - Neural Networks Part 2
Training Neural Networks Part 1 activation functions, weight initialization, gradient flow, batch normalization babysitting the learning process, hyperparameter optimization
From playlist CS231N - Convolutional Neural Networks
Professor Stéphane Mallat: "High-Dimensional Learning and Deep Neural Networks"
The Turing Lectures: Mathematics - Professor Stéphane Mallat: High-Dimensional Learning and Deep Neural Networks Click the below timestamps to navigate the video. 00:00:07 Welcome by Professor Andrew Blake, Director, The Alan Turing Institute 00:01:36 Introduction by Professo
From playlist Turing Lectures
A varifold approach to surface approximation and curvature (...) - Buet - Workshop 1 - CEB T1 2019
Buet (Univ. Paris Sud) / 07.02.2019 A varifold approach to surface approximation and curvature estimation on point clouds Joint work with: Gian Paolo Leonardi (Modena) and Simon Masnou (Lyon). We propose a natural framework for the study of surfaces and their different discretizations
From playlist 2019 - T1 - The Mathematics of Imaging
Discrete Math II - 8.2.3 General Case Linear Homogeneous Recurrence Relations
Now that we are familiar with solving second-order homogeneous recurrence relations, we extend our methods to higher-order homogeneous recurrence relations. You will find the methodology to be the same as in the last video. However, if you are out of practice on either solving polynomials
From playlist Discrete Math II/Combinatorics (entire course)
Lecture 14D : Modeling real-valued data with an RBM
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] Lecture 14D : Modeling real-valued data with an RBM
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]