Title: Symbolic-Numeric Computation with Rational Functions Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Mark Giesbrecht 4/23/15 Part 2
Title: I. Approximate Computation with Differential Polynomials: Approximate GCRDs II. Sparsity, Complexity and Practicality in Symbolic Computations Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Title: Computing real solutions to systems of polynomial equations using numerical algebraic geometry Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Title: Hybrid symbolic-numeric computation: a marriage made in heaven Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Mioara Joldes: Validated symbolic-numerci algorithms and practical applications in aerospace
In various fields, ranging from aerospace engineering or robotics to computer-assisted mathematical proofs, fast and precise computations are essential. Validated (sometimes called rigorous as well) computing is a relatively recent field, developed in the last 20 years, which uses numerica
From playlist Probability and Statistics
Title: Towards Soft Voronoi Diagrams Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Title: Numerical methods for investigating parameter spaces for parameterized polynomial systems Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Mark Giesbrecht 4/23/15 Part 1
Title: I. Approximate Computation with Differential Polynomials: Approximate GCRDs II. Sparsity, Complexity and Practicality in Symbolic Computations Symbolic-Numeric Computing Seminar
From playlist Symbolic-Numeric Computing Seminar
Reinhard Laubenbacher 11/09/17
Finite Dynamic Networks
From playlist Symbolic-Numeric Computing Seminar
NVIDIA Deep Learning Course: Class #4 - Getting started with Theano
Register for the full course and find the Q&A log at https://developer.nvidia.com/deep-learning-courses Theano is a Python library that allows you define, optimize, and evaluate symbolic mathematical expressions involving multi-dimensional arrays. This has made Theano ideally suited to de
From playlist Deep Neural Networks
For more training resources, visit: http://www.wolfram.com/training/ Solve differential and integral equations, optimization problems, curvilinear expressions, and more, faster and more easily using the cutting-edge enhancements to symbolic and numeric computation. Notebook link: https:
From playlist New in the Wolfram Language and Mathematica Version 11
How we represent numbers in computers. Part of a larger series teaching programming. Visit codeschool.org Twitter: @brianwill
From playlist Numbers as bits
Live CEOing Ep 20: MathematicalConstantData[] in the Wolfram Language
Watch Stephen Wolfram and teams of developers in a live, working, language design meeting. This episode is about MathematicalConstantData[] in the Wolfram Language.
From playlist Behind the Scenes in Real-Life Software Design
Q&A with Calculus Developers: Live with the R&D team
Presentation starts at 1:00 In this stream, Devendra and Daniel answer Calculus & Algebra give a glimpse of recent and upcoming features in symbolic calculus, many of which have been motivated by frequent requests from users and then answer related questions from the community." Follow us
From playlist Live with the R&D Team
Overview of equation solving tools notebooks
I talk over the different ways of solving equations in Python using SymPy and SciPy
From playlist Simulation
A New Kind of Numeric: Where Knowledge Meets Computation
To learn more about Wolfram Technology Conference, please visit: https://www.wolfram.com/events/technology-conference/ Speaker: Erdem Uguz Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and mo
From playlist Wolfram Technology Conference 2017
Maria Charina: Algebraic multigrid and subdivision
Abstract: Multigrid is an iterative method for solving large linear systems of equations whose Toeplitz system matrix is positive definite. One of the crucial steps of any Multigrid method is based on multivariate subdivision. We derive sufficient conditions for convergence and optimality
From playlist Numerical Analysis and Scientific Computing
Discovering Symbolic Models from Deep Learning with Inductive Biases (Paper Explained)
Neural networks are very good at predicting systems' numerical outputs, but not very good at deriving the discrete symbolic equations that govern many physical systems. This paper combines Graph Networks with symbolic regression and shows that the strong inductive biases of these models ca
From playlist Papers Explained
Overview of Numerical Computation
This talk will be an introduction to and summary of many of the numerical computation capabilities built into Mathematica, including arbitrary precision arithmetic, numerical linear algebra, optimization, integration, and differential equations.
From playlist Wolfram Technology Conference 2013
The P versus NP problem and the Tau conjecture
From playlist Fall 2018 Symbolic-Numeric Computing