Diophantine properties of Markoff numbers - Jean Bourgain
Using available results on the strong approximation property for the set of Markoff triples together with an extension of Zagier’s counting result, we show that most Markoff numbers are composite. For more videos, visit http://video.ias.edu
From playlist Mathematics
SinGAN Explained! (ICCV '19 Best Paper)
Paper Link: https://arxiv.org/pdf/1905.01164.pdf Animations (Video): https://www.youtube.com/watch?v=xk8bWLZk4DU&feature=youtu.be Pix2Pix (Markovian Discriminator): https://arxiv.org/pdf/1611.07004.pdf SinGAN demonstrates a remarkable ability to generate novel images from a single source
From playlist ICCV Research
Prob & Stats - Markov Chains (22 of 38) Absorbing Markov Chains - Example 2
Visit http://ilectureonline.com for more math and science lectures! In this video I will find the stable transition matrix in an absorbing Markov chain. Next video in the Markov Chains series: http://youtu.be/hMceS_HIcKY
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
Quantum feedback for measurement and control - L. Martin - PRACQSYS 2018 - CEB T2 2018
Leigh Martin (Quantum Nanoelectronics Laboratory, Department of Physics, University of California, Berkeley, USA & Center for Quantum Coherent Science, University of California, Berkeley, USA) / 06.07.2018 Quantum feedback for measurement and control Many fundamental quantum limits arise
From playlist 2018 - T2 - Measurement and Control of Quantum Systems: Theory and Experiments
Matrix Limits and Markov Chains
In this video I present a cool application of linear algebra in which I use diagonalization to calculate the eventual outcome of a mixing problem. This process is a simple example of what's called a Markov chain. Note: I just got a new tripod and am still experimenting with it; sorry if t
From playlist Eigenvalues
(ML 14.2) Markov chains (discrete-time) (part 1)
Definition of a (discrete-time) Markov chain, and two simple examples (random walk on the integers, and a oversimplified weather model). Examples of generalizations to continuous-time and/or continuous-space. Motivation for the hidden Markov model.
From playlist Machine Learning
(ML 14.1) Markov models - motivating examples
Introduction to Markov models, using intuitive examples of applications, and motivating the concept of the Markov chain.
From playlist Machine Learning
Prob & Stats - Markov Chains (8 of 38) What is a Stochastic Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a stochastic matrix. Next video in the Markov Chains series: http://youtu.be/YMUwWV1IGdk
From playlist iLecturesOnline: Probability & Stats 3: Markov Chains & Stochastic Processes
AI Weekly Update - April 27th, 2020 (#19)
Thanks for watching! Please Subscribe! Please check out Machine Learning Street Talk! https://www.youtube.com/channel/UCMLtBahI5DMrt0NPvDSoIRQ Chip Design with Reinforcement Learning: https://ai.googleblog.com/2020/04/chip-design-with-deep-reinforcement.html Jeff Dean ISSCC Keynote on The
From playlist AI Research Weekly Updates
(ML 18.4) Examples of Markov chains with various properties (part 1)
A very simple example of a Markov chain with two states, to illustrate the concepts of irreducibility, aperiodicity, and stationary distributions.
From playlist Machine Learning
Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of
From playlist COVARIANCE AND VARIANCE
(ML 14.3) Markov chains (discrete-time) (part 2)
Definition of a (discrete-time) Markov chain, and two simple examples (random walk on the integers, and a oversimplified weather model). Examples of generalizations to continuous-time and/or continuous-space. Motivation for the hidden Markov model.
From playlist Machine Learning
Exploring Quantum Physics using Spin Ensembles by T S Mahesh
21 November 2016 to 10 December 2016 VENUE Ramanujan Lecture Hall, ICTS Bangalore Quantum Theory has passed all experimental tests, with impressive accuracy. It applies to light and matter from the smallest scales so far explored, up to the mesoscopic scale. It is also a necessary ingredie
From playlist Fundamental Problems of Quantum Physics
Photon Correlations in Waveguide QED: Rectification... by Harold Baranger
Open Quantum Systems DATE: 17 July 2017 to 04 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore There have been major recent breakthroughs, both experimental and theoretical, in the field of Open Quantum Systems. The aim of this program is to bring together leaders in the Open Q
From playlist Open Quantum Systems
Thermodynamic uncertainty relation in quantum transport by Bijay Kumar Agarwalla
DISCUSSION MEETING INDIAN STATISTICAL PHYSICS COMMUNITY MEETING ORGANIZERS Ranjini Bandyopadhyay, Abhishek Dhar, Kavita Jain, Rahul Pandit, Sanjib Sabhapandit, Samriddhi Sankar Ray and Prerna Sharma DATE: 14 February 2019 to 16 February 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalo
From playlist Indian Statistical Physics Community Meeting 2019
Keldysh Field Theory for Open Quantum Systems: Localization and Quantum Effects by Rajdeep Sensarma
Open Quantum Systems DATE: 17 July 2017 to 04 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore There have been major recent breakthroughs, both experimental and theoretical, in the field of Open Quantum Systems. The aim of this program is to bring together leaders in the Open Q
From playlist Open Quantum Systems
Non-Markovian dynamics of a qubit due to single-photon by Ciccarello Francesco
Open Quantum Systems DATE: 17 July 2017 to 04 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore There have been major recent breakthroughs, both experimental and theoretical, in the field of Open Quantum Systems. The aim of this program is to bring together leaders in the Open Q
From playlist Open Quantum Systems
CICERO: An AI agent that negotiates, persuades, and cooperates with people
#ai #cicero #diplomacy A team from Meta AI has developed Cicero, an agent that can play the game Diplomacy, in which players have to communicate via chat messages to coordinate and plan into the future. Paper Title: Human-level play in the game of Diplomacy by combining language models
From playlist Papers Explained
Stochastic processes by VijayKumar Krishnamurthy
Winter School on Quantitative Systems Biology DATE: 04 December 2017 to 22 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The International Centre for Theoretical Sciences (ICTS) and the Abdus Salam International Centre for Theoretical Physics (ICTP), are organizing a Wint
From playlist Winter School on Quantitative Systems Biology
(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