Automatic differentiation: The most criminally underused tool in probabilistic numerics David Duvenaud Do we know the function we’re integrating?

Source URL: probabilistic-numerics.org

Posters at ADPatrick E. Farrell (Department of Earth Science and Engineering, Imperial College London, UK): Automating the adjoint of finite element discretisations In this work we demonstrate the capability of

Source URL: www.autodiff.org

• Mathematics
• Mathematical analysis
• Academia
• Operations research
• Differential calculus
• Automatic differentiation
• Computer algebra
• Applied mathematics
• Numerical analysis
• Finite element method
• Mathematical optimization
• Linear programming

JAR manuscript No. (will be inserted by the editor) Proving Tight Bounds on Univariate Expressions with Elementary Functions in Coq Érik Martin-Dorel · Guillaume Melquiond

Source URL: www.lri.fr

• Computer algebra
• Computer arithmetic
• Algebra
• Numerical analysis
• Polynomials
• Interval arithmetic
• Automatic differentiation
• Floating point
• Polynomial
• Remainder
• Symbolic computation
• Interval

Scaling up Gaussian Belief Space Planning through Covariance-Free Trajectory Optimization and Automatic Differentiation Sachin Patil, Gregory Kahn, Michael Laskey, John Schulman, Ken Goldberg, Pieter Abbeel University of

Source URL: goldberg.berkeley.edu

• Mathematical optimization
• Systems theory
• Engineering
• Systems science
• Control theory
• Robot control
• Operations research
• Optimal control
• Trajectory optimization
• Kalman filter
• Model predictive control
• Quadratic programming

Madness: a package for Multivariate Automatic Differentiation Steven E. Pav ∗

Source URL: mran.revolutionanalytics.com

389 Documenta Math. Who Invented the Reverse Mode of Differentiation?

Source URL: www.math.uiuc.edu

• Calculus
• Mathematical analysis
• Mathematics
• Multivariable calculus
• Differential calculus
• Mathematical optimization
• Automatic differentiation
• Computer algebra
• Differential equations
• Differential operator
• Partial differential equation
• Sheaf

JuMP: A MODELING LANGUAGE FOR MATHEMATICAL OPTIMIZATION IAIN DUNNING, JOEY HUCHETTE, MILES LUBIN ∗

Source URL: www.optimization-online.org

• Mathematical optimization
• Operations research
• Numerical software
• Computer algebra systems
• AMPL
• Algebraic modeling language
• Linear programming
• Gurobi
• Automatic differentiation
• Nl
• Pyomo
• SCIP

Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities Paul J. Werbos1 Abstract Backwards calculation of derivatives – sometimes called the reverse mode, the full adjoint method, or backpropa

Source URL: www.werbos.com

• Mathematics
• Neuroscience
• Backpropagation
• Artificial neural network
• Automatic differentiation
• Multilayer perceptron
• Perceptron
• Derivative
• Feedforward neural network
• Neural networks
• Computational neuroscience
• Cybernetics

Use of automatic differentiation (AD) in OPM Atgeirr Flø Rasmussen SINTEF ICT, Dept. Applied Mathematics 12th March 2015

Source URL: www.opm-project.org

An Example of an Automatic Differentiation-Based Modelling System Thomas Kaminski1 , Ralf Giering1 , Marko Scholze2 , Peter Rayner3 , and Wolfgang Knorr4 1

Source URL: www.fastopt.com