User:Waterbug89/Books/Stochastic applications, methods, algorithms

Stochastic applications, methods, algorithms

stochastic analysis

Arthur–Merlin protocol

Automatic basis function construction

Auxiliary field Monte Carlo

Auxiliary particle filter

Average-case complexity

Biology Monte Carlo method

Bloom filter

Construction of an irreducible Markov chain in the Ising model

Count–min sketch

Coupling from the past

Cross-entropy method

Datar–Mathews method for real option valuation

Derandomization

Diffusion Monte Carlo

Direct simulation Monte Carlo

Dynamic Monte Carlo method

Ensemble forecasting

Ensemble Kalman filter

Equation of State Calculations by Fast Computing Machines

Fisher–Yates shuffle

Gaussian quantum Monte Carlo

Gibbs sampling

Hybrid Monte Carlo

HyperLogLog

Inverse transform sampling

Iterated filtering

Kinetic Monte Carlo

Least mean squares filter

Linear partial information

Linear–quadratic–Gaussian control

List update problem

Low-energy adaptive clustering hierarchy

Mabinogion sheep problem

Markov chain Monte Carlo

Markov decision process

Marsaglia polar method

Mean field particle methods

Merton's portfolio problem

Metropolis light transport

Metropolis-adjusted Langevin algorithm

Monte Carlo algorithm

Monte Carlo integration

Monte Carlo localization

Monte Carlo method

Monte Carlo methods for option pricing

Monte Carlo methods in finance

Monte Carlo molecular modeling

Monte Carlo tree search

Morris method

Multi-armed bandit

Multiplier uncertainty

Natural evolution strategy

Neyer d-optimal test

Partially observable Markov decision process

Path integral Monte Carlo

PCP theorem

Pocock boundary

Principle of deferred decision

Quantum Monte Carlo

Quasi-Monte Carlo method

Quasi-Monte Carlo methods in finance

Quotient filter

Random binary tree

Random permutation

Random search

Random self-reducibility

Random tree

Rapidly-exploring random tree

Rejection sampling

Reptation Monte Carlo

Reservoir sampling

Response surface methodology

Reverse Monte Carlo

Reversible-jump Markov chain Monte Carlo

Scenario optimization

Separation principle

Set balancing

Simulated annealing

Simulation Optimization Library: Throughput Maximization

Simultaneous perturbation stochastic approximation

Sipser–Lautemann theorem

Slice sampling

Solovay–Strassen primality test

Stochastic approximation

Stochastic computing

Stochastic gradient descent

Stochastic neural network

Stochastic optimization

Stochastic tunneling

Stochastic universal sampling

Tau-leaping

Time-dependent variational Monte Carlo

Umbrella sampling

Variance reduction

Variational Monte Carlo

Volumetric path tracing

Wang and Landau algorithm

With high probability

Witsenhausen's counterexample

Yao's principle

Ziff–Gulari–Barshad model