Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field m...
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Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm.
An algorithm is described that will recognize, and fully analyze, strings of unbounded length, using the rewriting rules of any context-free grammar. It uses a finite random access store, three pushdown tapes, and a c...
An algorithm is described that will recognize, and fully analyze, strings of unbounded length, using the rewriting rules of any context-free grammar. It uses a finite random access store, three pushdown tapes, and a counter. It imposes no restrictions on the grammar defined by the rewriting rules, excepting only that it be a context-free phrase structure grammar. The analysis printed out is a linearized form of the structural description tree (or trees, in an ambiguous case) of the input string. A proof that the analyzer will always stop in a finite time is provided. The upper bound on the running time increases exponentially with input string length.
Phaser is a sophisticated program for IBM personal com-puters, developed atBrown University by the author and someof his students, which enables usersto experiment withdifferential and difference equations and dynamic...
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ISBN:
(数字)9781461236108
ISBN:
(纸本)9780387969183
Phaser is a sophisticated program for IBM personal com-
puters, developed atBrown University by the author and some
of his students, which enables usersto experiment with
differential and difference equations and dynamical systems
in an interactive environment using graphics. This book
begins with a brief discussion of the geometric inter-
pretation of differential equations and numerical methods,
and proceeds to guide the student through the use of the
program. To run Phaser, you need an IBM PC, XT, AT, or PS/2
with an IBM Color GRaphics Board (CGB), Enhanced Graphics
Adapter (VGA). A math coprocessor is supported; however, one
is not required for Phaser to run on the above hardware.
Two models of sedimentation in a density gradient are analyzed. The first is for sedimentation in cylindrical sector geometry and contains the assumption that diffusion can be neglected. The second treats sedimentatio...
Two models of sedimentation in a density gradient are analyzed. The first is for sedimentation in cylindrical sector geometry and contains the assumption that diffusion can be neglected. The second treats sedimentation in a rectangular field and includes diffusion, although the boundaries are not treated exactly. In both of these models we approximate the time dependence of the gradient by a relaxation form. We derive exact results for both models. It is also shown that the sedimentation coefficient can be calculated from data by following the motion of the position of the maximum (or minimum) of the concentration gradient.
We present the results of accurate numerical solutions to the Lamm equation, including the effects of hydrostatic pressure, in order to check methods for the estimation of parameters based on a diffusionless theory. S...
We present the results of accurate numerical solutions to the Lamm equation, including the effects of hydrostatic pressure, in order to check methods for the estimation of parameters based on a diffusionless theory. Some estimates of boundary spreading due to diffusion are given. The results indicate that parameter estimates based on the position of the maximum concentration gradient lead to fairly accurate results.
The question as to the correct block exit strategy, retention or deletion, is resolved by formally comparing the contour model and the stack model, each of which implements one of the strategies, to the copy rule, a f...
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This book contains expanded versions of research papers presented at the international sessions of Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), which was held online in June 2020. The ...
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ISBN:
(数字)9783030731137
ISBN:
(纸本)9783030731120
This book contains expanded versions of research papers presented at the international sessions of Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), which was held online in June 2020. The JSAI annual conferences are considered key events for our organization, and the international sessions held at these conferences play a key role for the society in its efforts to share Japan’s research on artificial intelligence with other countries. In recent years, AI research has proved of great interest to business people. The event draws both more and more presenters and attendees every year, including people of diverse backgrounds such as law and the social sciences, in additional to artificial intelligence. We are extremely pleased to publish this collection of papers as the research results of our international sessions.
This book constitutes the joint refereed proceedings of the 4th International Workshop on Approximation Algorithms for Optimization Problems, APPROX 2001 and of the 5th International Workshop on Ranomization and Appro...
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ISBN:
(数字)9783540446668
ISBN:
(纸本)9783540424703
This book constitutes the joint refereed proceedings of the 4th International Workshop on Approximation Algorithms for Optimization Problems, APPROX 2001 and of the 5th International Workshop on Ranomization and Approximation Techniques in computerscience, RANDOM 2001, held in Berkeley, California, USA in August 2001. The 26 revised full papers presented were carefully reviewed and selected from a total of 54 submissions. Among the issues addressed are design and analysis of approximation algorithms, inapproximability results, on-line problems, randomization, de-randomization, average-case analysis, approximation classes, randomized complexity theory, scheduling, routing, coloring, partitioning, packing, covering, computational geometry, network design, and applications in various fields.
This paper presents well-conditioned rational Chebyshev approximations, involving at most one exponentiation, for computation of either (Xs) 55, for up to 20 significant figures. The logarithmic error is required in o...
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Simulation-based methods for statistical inference have evolved dramatically over the past 50 years, keeping pace with technological advancements. The field is undergoing a new revolution as it embraces the representa...
Simulation-based methods for statistical inference have evolved dramatically over the past 50 years, keeping pace with technological advancements. The field is undergoing a new revolution as it embraces the representational capacity of neural networks, optimization libraries, and graphics processing units for learning complex mappings between data and inferential targets. The resulting tools are amortized, in the sense that, after an initial setup cost, they allow rapid inference through fast feed-forward operations. In this article we review recent progress in the context of point estimation, approximate Bayesian inference, summary-statistic construction, and likelihood approximation. We also cover software and include a simple illustration to showcase the wide array of tools available for amortized inference and the benefits they offer over Markov chain Monte Carlo methods. The article concludes with an overview of relevant topics and an outlook on future research directions.
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