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Every blot's an inspiration Every line is free Unlock your
imagination Draw what you see Hirameki - 'brainwave' or 'flash of
inspiration' in Japanese - is where doodling and imagination come
together. Simply put, it's the art of turning a random blot into
something amazing, just by adding a few dots and lines. If it's
true that you can find happiness in little things, this book should
keep your eyes, hand and brain entertained for hours.
36 placemats for mealtime doodling fun!
Draw funny dogs and get into a sunny mood. Draw comical cats and
give your day a boost. If you feel like fun and have a pen. It's
time to follow your imagination!. Hirameki - 'brainwave' or 'flash
of inspiration' in Japanese - is where doodling and imagination
come together. Simply put, it's the art of turning a random blot
into something amazing, just by adding a few dots and lines. If
it's true that you can find happiness in little things, this book
should keep your eyes, hand and brain entertained for hours.
Every sky's an inspiration, Every cloud floats free, Unlock your
imagination, Draw what you see! Hirameki - 'brainwave' or 'flash of
inspiration' in Japanese - is where doodling and imagination come
together. Simply put, it's the art of turning a random blot into
something amazing, just by adding a few dots and lines. If it's
true that you can find happiness in little things, this book should
keep your eyes, hand and brain entertained for hours.
Numerical methods in finance have emerged as a vital field at the
crossroads of probability theory, finance and numerical analysis.
Based on presentations given at the workshop Numerical Methods in
Finance held at the INRIA Bordeaux (France) on June 1-2, 2010, this
book provides an overview of the major new advances in the
numerical treatment of instruments with American exercises.
Naturally it covers the most recent research on the mathematical
theory and the practical applications of optimal stopping problems
as they relate to financial applications. By extension, it also
provides an original treatment of Monte Carlo methods for the
recursive computation of conditional expectations and solutions of
BSDEs and generalized multiple optimal stopping problems and their
applications to the valuation of energy derivatives and assets. The
articles were carefully written in a pedagogical style and a
reasonably self-contained manner. The book is geared toward
quantitative analysts, probabilists, and applied mathematicians
interested in financial applications.
Numerical methods in finance have emerged as a vital field at the
crossroads of probability theory, finance and numerical analysis.
Based on presentations given at the workshop Numerical Methods in
Finance held at the INRIA Bordeaux (France) on June 1-2, 2010, this
book provides an overview of the major new advances in the
numerical treatment of instruments with American exercises.
Naturally it covers the most recent research on the mathematical
theory and the practical applications of optimal stopping problems
as they relate to financial applications. By extension, it also
provides an original treatment of Monte Carlo methods for the
recursive computation of conditional expectations and solutions of
BSDEs and generalized multiple optimal stopping problems and their
applications to the valuation of energy derivatives and assets. The
articles were carefully written in a pedagogical style and a
reasonably self-contained manner. The book is geared toward
quantitative analysts, probabilists, and applied mathematicians
interested in financial applications.
This book presents some new concentration inequalities for
Feynman-Kac particle processes. It analyzes different types of
stochastic particle models, including particle profile occupation
measures, genealogical tree based evolution models, particle free
energies, as well as backward Markov chain particle models. It
illustrates these results with a series of topics related to
computational physics and biology, stochastic optimization, signal
processing and Bayesian statistics, and many other probabilistic
machine learning algorithms. Special emphasis is given to the
stochastic modeling, and to the quantitative performance analysis
of a series of advanced Monte Carlo methods; including particle
filters, genetic type island models, Markov bridge models, and
interacting particle Markov chain Monte Carlo methodologies.
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