Nicolás García Trillos: "From clustering with graph cuts to isoperimetric inequalities..."
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop II: PDE and Inverse Problem Methods in Machine Learning "From clustering with graph cuts to ...
Institute for Pure & Applied Mathematics (IPAM)
Yann LeCun - Graph Embedding, Content Understanding, and Self-Supervised Learning
Institut des Hautes Études Scientifiques (IHÉS)
Week 5-3 Interpolation Application - MATH/MTHE 272
Alan Ableson
Wilkinson, Numerical Analysis, and Me - Nick Trefethen, May 29, 2019
A talk by Nick Trefethen at the workshop Advances in Numerical Linear Algebra, May 29-30, 2019 held in the School of Mathematics at the University of ...
nla-group
Latent Stochastic Differential Equations | David Duvenaud
A talk from the Toronto Machine Learning Summit: https://torontomachinelearning.com/ The video is hosted by https://towardsdatascience.com/ About the ...
Towards Data Science
Lecture 8 - Data Splits, Models & Cross-Validation | Stanford CS229: Machine Learning (Autumn 2018)
Take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program. Learn more at: https://stanford.io/3bhmLce Andrew Ng ...
stanfordonline
Quaternions and 3d rotation, explained interactively
Go experience the explorable videos: https://eater.net/quaternions Ben Eater's channel: https://www.youtube.com/user/eaterbc Brought to you by you: ...
3Blue1Brown
Non-Linear CURVE FITTING using PYTHON
A tutorial on how to perform a non-linear curve fitting of data-points to any arbitrary function with multiple fitting parameters. I use the script package and the ...
Phys Whiz
GRCon17 - Symbol Clock Recovery and Improved Symbol Synchronization Blocks - Andy Walls
Slides available here: ...
GNU Radio
Nonlinear Regression: Exponential Model
Learn via an example an exponential nonlinear regression model. For more videos and resources on this topic, please visit ...
numericalmethodsguy
Jon Keating: Random matrices, integrability, and number theory - Lecture 1
Abstract: I will give an overview of connections between Random Matrix Theory and Number Theory, in particular connections with the theory of the Riemann ...
Centre International de Rencontres Mathématiques
Dynamic Mode Decomposition from Koopman Theory to Applications (Prof. Peter J. Schmid)
This lecture was given by Prof. Peter J. Schmid, Imperial College London, UK in the framework of the von Karman Lecture Series on Machine Learning for Fluid ...
von Karman Institute for Fluid Dynamics
Harmonic measure: Algorithms and applications – Christopher Bishop – ICM2018
Analysis and Operator Algebras Invited Lecture 8.12 Harmonic measure: Algorithms and applications Christopher Bishop Abstract: This is a brief survey of ...
Rio ICM2018
The Ellipsoid Algorithm || @ CMU || Lecture 19a of CS Theory Toolkit
The Ellipsoid Algorithm (sketched): solving Linear Programming in polynomial time, or convex optimization with just a separation oracle. Lecture 19a of "CS ...
Ryan O'Donnell
DOE CSGF 2016: The Deterministic Information Bottleneck
View more information on the DOE CSGF Program at http://www.krellinst.org/csgf Compression fundamentally involves a decision about what is relevant and ...
Krell Institute
Chebfun
Chebfun is a Matlab-based open-source software project for "numerical computing with functions" based on algorithms related to Chebyshev polynomials.
Society for Industrial and Applied Mathematics
MIA: Geoffrey Schiebinger, Learning developmental landscapes with optimal transport; Lénaïc Chizat
September 27, 2017 Meeting: https://youtu.be/vJx7NiXFMi8?t=2499 Geoffrey Schiebinger Broad Institute, MIT Statistics Learning developmental landscapes ...
Broad Institute
Dragan Djuric - Interactive GPU programming with ClojureCUDA & ClojureCL | Code Mesh LDN 18
This video was recorded at Code Mesh LDN 18 http://bit.ly/2P7SPII Get involved in Code Sync's next conference http://bit.ly/2Mcm4aS --- INTERACTIVE GPU ...
Code Sync
Riccardo Zecchina: "Evidence for local entropy optimization in machine learning, physics and neu..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "Evidence for local entropy ...
Institute for Pure & Applied Mathematics (IPAM)
Sparse Polynomial Interpolation: Compressed Sensing, Super-resolution, or Prony?
Jean-Bernard Lasserre, CNRS https://simons.berkeley.edu/talks/jean-bernard-lasserre-11-6-17 Hierarchies, Extended Formulations and Matrix-Analytic ...
Simons Institute
Introduction to Quantum Chemistry
Bryan O'Gorman (UC Berkeley/NASA Ames) https://simons.berkeley.edu/talks/tbd-116 The Quantum Wave in Computing Boot Camp.
Simons Institute
The Importance of Better Models in Stochastic Optimization...
John Duchi (Stanford University) https://simons.berkeley.edu/talks/tbd-28 Robust and High-Dimensional Statistics.
Simons Institute
Curve Fitting Of Exponential Curve By Least Square Method Examples
This video lecture of Curve Fitting Of Exponential Curve By Least Square Method | Example & Solution by GP Sir will help Engineering and Basic Science ...
Dr.Gajendra Purohit
A geometric view on Iwasawa theory - Mladen Dimitrov
Joint IAS/Princeton University Number Theory Seminar Topic: A geometric view on Iwasawa theory Speaker: Mladen Dimitrov Affiliation: Université de Lille Date: ...
Institute for Advanced Study
Simulating the Quantum World on a Classical Computer
A Google TechTalk, 10/6/16, presented by Garnet Chan ABSTRACT: Quantum mechanics is the fundamental theory underlying all of chemistry, materials ...
GoogleTechTalks
Quantum-Inspired Classical Linear Algebra
Ewin Tang (University of Washington) https://simons.berkeley.edu/talks/tbd-119 The Quantum Wave in Computing Boot Camp.
Simons Institute
Data Science - Part XVI - Fourier Analysis
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations ...
Derek Kane
The Power and Limitations of Kernel Learning
Misha Belkin, Ohio State University https://simons.berkeley.edu/talks/misha-belkin-11-30-17 Optimization, Statistics and Uncertainty.
Simons Institute
Quantum Supremacy II
Adam Bouland (UC Berkeley) https://simons.berkeley.edu/talks/clone-tbd-0 The Quantum Wave in Computing Boot Camp.
Simons Institute
Diaconis Persi "Poincaré's Probability"
Résumé Poincaré's contributions to probability are few but fine. He studied its foundations (Poincaré's roulette argument), introduced average case analysis for ...
Institut Henri Poincaré
JuliaCon 2017 | The Unique Features and Performance of DifferentialEquations.jl | Chris Rackauckas
CHRIS RACKAUCKAS, UNIVERSITY OF CALIFORNIA, IRVINE DifferentialEquations.jl is a highly extendable high-performance library for solving a vast array of ...
The Julia Programming Language
David Woodruff - Sketching as a Tool for Numerical Linear Algebra
David Woodruff presents as part of the UBC Department of Computer Science's Distinguished Lecture Series, March 6, 2014. I will discuss how sketching ...
UBC_CS
Polynomial Regression Model Example Part 1 of 2
Learn via example how to conduct polynomial regression. For more videos and resources on this topic, please visit ...
numericalmethodsguy
Reconstructing Continuous Signals via Leverage Score Sampling
Chris Musco (Princeton University) https://simons.berkeley.edu/talks/reconstructing-continuous-signals-leverage-score-sampling Randomized Numerical Linear ...
Simons Institute
"Why do tree ensembles work?" by Joe Ross
Ensembles of decision trees (e.g., the random forest and AdaBoost algorithms) are powerful and well-known methods of classification and regression. This talk ...
Strange Loop
Differentiation of Discrete Functions: Newton Divided Difference Approach: Example
Learn via an example how the Newton's divided difference polynomial method is used to differentiate discrete functions. For more videos and resources on this ...
numericalmethodsguy
CUR Factorization via Discrete Empirical Interpolation by Mark Embree
The Discrete Empirical Interpolation Method (DEIM) of Chaturantabut and Sorensen (2010) has proved to be an essential technique in the reduction of ...
MMDS Foundation
MagLab Theory Winter School 2018: Duncan Haldane - Bipartite Entanglement I
The National MagLab held it's sixth Theory Winter School in Tallahassee, FL from January 8th - 13th, 2018.
National MagLab
CS885 Lecture 7a: Policy Gradient
Pascal Poupart
James Sethna - “Sloppy models, Differential geometry, and How Science Works”
Stanford University APPLIED PHYSICS/PHYSICS COLLOQUIUM Tuesday, February 20, 2018 4:30 p.m. on campus in Hewlett Teaching Center, Rm. 201 James ...
Stanford Physics
9.520/6.860: Statistical Learning Theory and Applications - Class 4
Prof. Lorenzo Rosasco, University of Genoa / MIT.
MITCBMM
Gerald V. Dunne - Resurgence and Phase Transitions
Institut des Hautes Études Scientifiques (IHÉS)
