Download Automatic Differentiation: Applications, Theory, and by H. Martin Bücker, George Corliss, Paul Hovland, Uwe Naumann, PDF

By H. Martin Bücker, George Corliss, Paul Hovland, Uwe Naumann, Boyana Norris

This assortment covers the state-of-the-art in computerized differentiation conception and perform. Practitioners and scholars will find out about advances in automated differentiation thoughts and techniques for the implementation of sturdy and robust instruments. Computational scientists and engineers will enjoy the dialogue of purposes, which supply perception into powerful options for utilizing computerized differentiation for layout optimization, sensitivity research, and uncertainty quantification.

Show description

Read or Download Automatic Differentiation: Applications, Theory, and Implementations PDF

Best counting & numeration books

Meshfree methods for partial differential equations IV

The numerical therapy of partial differential equations with particle tools and meshfree discretization strategies is a truly energetic learn box either within the arithmetic and engineering neighborhood. as a result of their independence of a mesh, particle schemes and meshfree equipment can take care of huge geometric adjustments of the area extra simply than classical discretization options.

Harmonic Analysis and Partial Differential Equations

The programme of the convention at El Escorial integrated four major classes of 3-4 hours. Their content material is mirrored within the 4 survey papers during this quantity (see above). additionally incorporated are the 10 45-minute lectures of a extra really expert nature.

Combinatorial Optimization in Communication Networks

This e-book supplies a entire presentation of state-of-the-art examine in communique networks with a combinatorial optimization part. the target of the booklet is to strengthen and advertise the speculation and functions of combinatorial optimization in verbal exchange networks. each one bankruptcy is written through knowledgeable facing theoretical, computational, or utilized facets of combinatorial optimization.

Extra resources for Automatic Differentiation: Applications, Theory, and Implementations

Example text

Harvard responded as follows to this proposal and to later discussions. First, they would not allow ANNs as such to be a major part of the thesis, since I had not found anyone willing to act as a mentor for that part. D. D. Third, they had some skepticism about reverse differentiation itself, and they wanted a really solid, clear, rigorous proof of its validity in the general case. D. if, in addition, I could show that the use of the reverse method would allow me to use more sophisticated time-series prediction methods which, in turn, would lead to the first successful implementation of Karl Deutsch’s model of nationalism and social communications [146].

What a Supervised Learning System (SLS) does. Minsky’s book was best known for arguing that 1) we need to use an MLP with a hidden layer even to represent simple nonlinear functions such as the XOR mapping; and 2) no one on earth had found a viable way to train MLPs with hidden layers good enough even to learn such simple functions. Minsky’s book convinced most of the world that neural networks were a discredited dead-end – the worst kind of heresy. Widrow has stressed that this pessimism, which squashed the early “perceptron” school of AI, should not really be blamed on Minsky.

Gov Summary. Backwards calculation of derivatives – sometimes called the reverse mode, the full adjoint method, or backpropagation – has been developed and applied in many fields. This paper reviews several strands of history, advanced capabilities and types of application – particularly those which are crucial to the development of brain-like capabilities in intelligent control and artificial intelligence. Key words: Reverse mode, backpropagation, intelligent control, reinforcement learning, neural networks, MLP, recurrent networks, approximate dynamic programming, adjoint, implicit systems 1 Introduction and Summary Backwards differentiation or “the reverse accumulation of derivatives” has been used in many different fields, under different names, for different purposes.

Download PDF sample

Rated 4.74 of 5 – based on 47 votes