Transference is a very useful word from psychoanalysis which describes the process whereby we react to situations in the present according to a pattern laid down in the past, usually in childhood. Getting to know our own particular transferences is part of becoming a sane adult. If you lik
From playlist RELATIONSHIPS
Transfer Functions: Introduction and Implementation
In this video we introduce transfer functions and show how they can be derived from a set of linear, ordinary differential equations. We also examine how to use a transfer function to predict the output of system to a given input. Topics and time stamps: 0:38 – Example using an aircraft
From playlist Control Theory
What is Transference And Why It Matters
Transference is a psychological phenomenon whereby we ‘transfer’ a way of behaving from childhood into adulthood – in situations which don’t really warrant it. It’s a big cause of trouble in relationships. If you like our films, take a look at our shop (we ship worldwide): https://goo.gl/U
From playlist RELATIONSHIPS
A (somewhat) new paradigm for mathematics and physics | Diffusion Symmetry 1 | N J Wildberger
The current understanding of symmetry in mathematics and physics is through group theory. However in the last 120 years, a new strand of thought has gradually appeared in a number of disciplines, from as varied as character theory, strongly regular graphs, von Neumann algebras, Hecke algeb
From playlist Diffusion Symmetry: A bridge between mathematics and physics
What are Transfer Functions? | Control Systems in Practice
This video introduces transfer functions - a compact way of representing the relationship between the input into a system and its output. It covers why transfer functions are so popular and what they are used for. Learn more: - MATLAB Tech Talk: 4 Ways to Implement a Transfer Function in
From playlist Control Systems in Practice
Set Theory (Part 6): Equivalence Relations and Classes
Please feel free to leave comments/questions on the video and practice problems below! In this video, I set up equivalence relations and the canonical mapping. The idea of equivalence relation will return when we construct higher-level number systems, e.g.integers, from the natural number
From playlist Set Theory by Mathoma
Equilibrium occurs when the overall state of a system is constant. Equilibrium can be static (nothing in the system is changing), or dynamic (little parts of the system are changing, but overall the state isn't changing). In my video, I'll demonstrate systems in both types of equilibrium,
From playlist Physics
Modularity, Attention and Credit Assignment...computations - Anirudh Goyal
More videos on http://video.ias.edu
From playlist Mathematics
Equivalence Relations Definition and Examples
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Equivalence Relations Definition and Examples. This video starts by defining a relation, reflexive relation, symmetric relation, transitive relation, and then an equivalence relation. Several examples are given.
From playlist Abstract Algebra
Symmetric Groups (Abstract Algebra)
Symmetric groups are some of the most essential types of finite groups. A symmetric group is the group of permutations on a set. The group of permutations on a set of n-elements is denoted S_n. Symmetric groups capture the history of abstract algebra, provide a wide range of examples in
From playlist Abstract Algebra
Junction Tree Variational Autoencoder for Molecular Graph Generation | TDLS
Toronto Deep Learning Series, 24 September 2018 For slides and more information, visit https://tdls.a-i.science/events/2018-09-24/ Paper Review: https://arxiv.org/abs/1802.04364 Speaker: Rouzbeh Afrasiabi (Multiple Sclerosis Society of Canada) Organizer: https://www.linkedin.com/in/ami
From playlist Machine Learning for Scientific Discovery
Jason Morton: "An Algebraic Perspective on Deep Learning, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "An Algebraic Perspective on Deep Learning, Pt. 2" Jason Morton, Pennsylvania State University Institute for Pure and Applied Mathematics, UCLA July 20, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-scho
From playlist GSS2012: Deep Learning, Feature Learning
How the brain controls the body | The Royal Society
In his Ferrier Lecture 2021, Professor Daniel Wolpert explores the amazing processes by which the brain controls the body. The effortless ease with which we move our arms, our eyes, even our lips when we speak masks the true complexity of the control processes involved. This is evident wh
From playlist Latest talks and lectures
Network Analysis. Lecture 16. Social learning
Social learning in networks. DeGroot model. Reaching consensus. Influence vector. Social influence networks. Lecture slides: http://www.leonidzhukov.net/hse/2015/networks/lectures/lecture16.pdf
From playlist Structural Analysis and Visualization of Networks.
Keynote: The New Era in NLP | SciPy 2019 | Rachel Thomas
In the past year, we have seen a remarkable number of breakthroughs in the field of natural language processing, including huge leaps forward in classifying, generating, and translating text. I will share a survey of the field, how it is changing, and what you need to know to get involved.
From playlist Rachel Thomas videos
Carlo Baldassi: "On the existence of wide flat minima in neural network landscapes: analytic and..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "On the existence of wide flat minima in neural network landscapes: analytic and algorithm approaches" Carlo Baldassi - Bocconi University Abstract: The techniques c
From playlist Machine Learning for Physics and the Physics of Learning 2019
Ruslan Salakhutdinov: "Advanced Hierarchical Models"
Graduate Summer School 2012: Deep Learning, Feature Learning "Advanced Hierarchical Models" Ruslan Salakhutdinov Institute for Pure and Applied Mathematics, UCLA July 24, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-school-deep-learning-fe
From playlist GSS2012: Deep Learning, Feature Learning
Scalable hyperparameter transfer learning - Perrone - Workshop 3 - CEB T1 2019
Valerio Perrone (Amazon) / 01.04.2019 Scalable hyperparameter transfer learning. Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization, such as hyperparameter optimization. Typically, BO relies on conventional Gaussian process (GP) regres
From playlist 2019 - T1 - The Mathematics of Imaging
Samuel Bowles, Research Professor at the Santa Fe Institute and Professor of Economics at the University of Siena, gave three public lectures where he presented evidence that explicit incentives and constraints often diminish ethical motivations. This is the third lecture of a three-part
From playlist Ethics, Politics and Economics
Set Theory Proof: Prove that the Relative Complement Distributes over the Intersection of Sets
Set Theory Proof: Prove that the Relative Complement Distributes over the Intersection of Sets If you enjoyed this video please consider liking, sharing, and subscribing. Udemy Courses Via My Website: https://mathsorcerer.com My FaceBook Page: https://www.facebook.com/themathsorcerer T
From playlist Set Theory