• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Investigating circadian rhythmicity in pain sensitivity using
Investigating circadian rhythmicity in pain sensitivity using

Deep neural networks - Cambridge Neuroscience
Deep neural networks - Cambridge Neuroscience

... The following Primer section introduces the basics of neural network models, including their learning algorithms and universal representational capacity. The section Feedforward neural networks for visual object recognition describes the specific large-scale object recognition networks that current ...
Audio Compression
Audio Compression

... A query by humming system Two-dimensional: pitch and rhythm Comparison between string-alignment (edit cost) dynamic programming and HMM algorithms (each theme represented as a model) Also compared to human performance Results ...
NUS at DUC 2007 - National University of Singapore
NUS at DUC 2007 - National University of Singapore

... • S.N. Dorogovtsev and J.F.F. Mendes. 2001. Evolution of networks. Submitted to Advances in Physics on 6th March 2001. • Sergey Brin and Lawrence Page. 1998. The anatomy of a large-scale hypertextual Web search engine. Com-puter Networks and ISDN Systems, 30(1-7). • Jon M. Kleinberg. 1999. Authorita ...
Using Semantic Cues to Learn Syntax
Using Semantic Cues to Learn Syntax

Aalborg Universitet Learning dynamic Bayesian networks with mixed variables Bøttcher, Susanne Gammelgaard
Aalborg Universitet Learning dynamic Bayesian networks with mixed variables Bøttcher, Susanne Gammelgaard

Practical Issues in Modeling Large Diagnostic Systems with Multiply
Practical Issues in Modeling Large Diagnostic Systems with Multiply

Induction and Recursion - Bryn Mawr Computer Science
Induction and Recursion - Bryn Mawr Computer Science

Synthesizing Robust Plans under Incomplete Domain Models
Synthesizing Robust Plans under Incomplete Domain Models

A  Probabilistic Model  of  Lexical and Syntactic DANIEL JURAFSKY
A Probabilistic Model of Lexical and Syntactic DANIEL JURAFSKY

VARIABLE BINDING IN BIOLOGICALLY PLAUSIBLE NEURAL
VARIABLE BINDING IN BIOLOGICALLY PLAUSIBLE NEURAL

Representing and Querying Correlated Tuples in Probabilistic
Representing and Querying Correlated Tuples in Probabilistic

... Probabilistic databases have received considerable attention recently due to the need for storing uncertain data produced by many real world applications. The widespread use of probabilistic databases is hampered by two limitations: (1) current probabilistic databases make simplistic assumptions abo ...
Dynamic `frees: A Structured Variational Method Giving Efficient
Dynamic `frees: A Structured Variational Method Giving Efficient

... Given this, it would appear sensible to model objects hierarchically. A simple deterministic model will not capture the variability in object structure between dif­ ferent images or parts of images, thus a probabilistic model is more appropriate. Using a tree-structured directed graph (see figure 1) ...
Auditory Nerve Stochasticity Impedes Category Learning: the Role
Auditory Nerve Stochasticity Impedes Category Learning: the Role

Temporal Dynamics of User Interests in Tagging
Temporal Dynamics of User Interests in Tagging

Let`s Do Algebra Tiles
Let`s Do Algebra Tiles

Secondary English Language Arts
Secondary English Language Arts

... 7.A.3.1 Create scale models and use them for dimensional drawings. 7.A.3.2 Understand and use the coordinate plane to graph ordered pairs and linear equations. 7.A.3.3 Select and use an appropriate model for a particular situation. 5-8 Benchmark A.4: 7.A.4.1 Use variables and appropriate operations ...
Progression in Teaching and Learning Multiplying and Dividing
Progression in Teaching and Learning Multiplying and Dividing

Towards the Theory-Guided Design of Help
Towards the Theory-Guided Design of Help

discrete variational autoencoders
discrete variational autoencoders

Partially observable Markov decision processes for
Partially observable Markov decision processes for

... Figure 2. The POMDP model. Arrows indicate probabilistic influence. The parameter S is a set containing the discrete states in which the environment can exist. In the TIS, the state of the environment is a representation of the key in which the musician is playing. There are 25 states, one for each ...
Statistical Script Learning with Multi
Statistical Script Learning with Multi

Let`s Do Algebra Tiles
Let`s Do Algebra Tiles

STANDARDS FOR MATHEMATICS High School Algebra 1
STANDARDS FOR MATHEMATICS High School Algebra 1

... tools might include pencil and paper, concrete models, a ruler, a protractor, a calculator, a spreadsheet, a computer algebra system, a statistical package, or dynamic geometry software. High school students should be sufficiently familiar with tools appropriate for their grade or course to make sou ...
Week of 2-13-17 - Math
Week of 2-13-17 - Math

< 1 ... 14 15 16 17 18 19 20 21 22 ... 68 >

Mathematical model

A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physics, biology, earth science, meteorology) and engineering disciplines (such as computer science, artificial intelligence), as well as in the social sciences (such as economics, psychology, sociology, political science). Physicists, engineers, statisticians, operations research analysts, and economists use mathematical models most extensively. A model may help to explain a system and to study the effects of different components, and to make predictions about behaviour.Mathematical models can take many forms, including but not limited to dynamical systems, statistical models, differential equations, or game theoretic models. These and other types of models can overlap, with a given model involving a variety of abstract structures. In general, mathematical models may include logical models. In many cases, the quality of a scientific field depends on how well the mathematical models developed on the theoretical side agree with results of repeatable experiments. Lack of agreement between theoretical mathematical models and experimental measurements often leads to important advances as better theories are developed.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report