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Machine Learning
This page contains resources about Pattern Recognition, Computational Statistics and Machine Learning in general. More specific information is included in each subfield. 
Statistical Signal Processing
This page contains resources about Statistical Signal Processing, including Statistical Modelling, Spectral Estimation, Point Estimation, Estimation Theory, Adaptive Filtering, Adaptive Signal Processing, Adaptive Filter Theory, Adaptive Array Processing and System Identification. See also Signal Processing 
Computational Finance
This page contains resources about Computational Finance, including Financial Engineering, Mathematical Finance, Quantitative Finance and Financial Econometrics. Subfields and Concepts[edit edit source] Binomial Options Pricing Model, Black–Scholes Model, Capital Asset Pricing Model (CAPM 
Optimization
This page contains resources about Mathematical Optimization, Computational Optimization and Operations Research. More specific information is included in each subfield. 
Product Management
This page contains resources about Product Management, Digital Product Management and Software Product Management. General[edit edit source] Lean Product Management, Agile Product Management, Stakeholder Management, Product Lifecycle (PLC) Phase 1: Introduction Phase 2: Growth 
Data Science
This page contains resources about Data Science, Data Engineering and Data Management. Subfields and Concepts[edit edit source] Agile Data Science, Machine Learning/ Data Mining, Exploratory Data Analysis (EDA), Data Preparation and Data Preprocessing, Data 
Probability and Statistics
This page contains resources about Probability Theory and Statistics in general. More specific information is included in each subfield. 
Variational Method
This page contains resources about Variational Methods and Variational Bayesian Inference. Subfields and Concepts[edit edit source] Variational Calculus/ Calculus of Variations, Variational Analysis, Variational free energy, Free energy principle, Conjugate Duality, Exponential family, Conjugate 
Probabilistic Graphical Model
This page contains resources about Probabilistic Graphical Models, Probabilistic Machine Learning and Probabilistic Models, including Latent Variable Models. Bayesian and nonBayesian approaches can either be used. 
Deep Learning
This page contains resources about Deep Learning and Representation Learning. Subfields and Concepts[edit edit source] Deep Generative Models Deep Directed Networks (directed graphical models) Sigmoid Belief Net Differentiable Generator Net Variational Autoencoder (VAE) Generative 
Information Theory
This page contains resources about Information Theory in general. More specific information is included in each subfield. 
Dimensionality Reduction
This page contains resources about Dimensionality Reduction, Model Order Reduction, Blind Signal Separation, Source Separation, Subspace Learning, and Continuous Latent Variable Models. Subfields and Concepts[edit edit source] Supervised Dimensionality Reduction Linear Discriminant Analysis (LDA 
Artificial Neural Network
This page contains resources about Artificial Neural Networks. For temporal (Time Series) and atemporal Sequential Data, please check Linear Dynamical Systems. 
Compressed Sensing
This page contains resources about Compressed Sensing, Sparse Sampling and Sparse Signal Processing. Subfields and Concepts[edit edit source] Incoherence/ Incoherent Sampling/ Incoherent bases Canonical/Kroneker basis Fourier basis Random basis Random sequences/ codes Inverse 
Control Theory
This page contains resources about Control Theory, Dynamical Systems Theory and Dynamical Systems in general. More specific information is included in each subfield. 
Linear Dynamical System
This page contains resources about Linear Dynamical Systems, Linear Systems Theory, Dynamic Linear Models, Linear State Space Models and StateSpace Representation, including temporal (Time Series) and atemporal Sequential Data. Subfields and Concepts[edit edit 
Computer Vision
This page contains resources about Computer Vision, Machine Vision and Image Processing in general. More specific information is included in each subfield. 
Bayesian Nonparametrics
This page contains resources about Bayesian Nonparametrics. See Category:Bayesian Nonparametrics for some of its subfields. Nonparametric Empirical Bayes (NPEB) Method, Gamma Process Nonnegative Matrix Factorization, Gaussian Process, Dirichlet Process 
Signal Processing
This page contains resources about Signal Processing in general. More specific information is included in each subfield. 
Statistical Learning Theory
This page contains resources about Statistical Learning Theory and Computational Learning Theory. Subfields and Concepts[edit edit source] Asymptotics, VapnikChervonenkis(VC) Theory VC dimension Symmetrization Chernoff Bounds, VC dimension, Symmetrization, Chernoff Bounds, Kernel Methods 
Robotics
This page contains resources about Robotics in general. More specific information is included in each subfield. 
Bayesian Machine Learning
This page contains resources about Bayesian Inference and Bayesian Machine Learning. Bayesian Networks do not necessarily follow Bayesian approach, but they are named after Bayes' Rule. 
Computational Neuroscience
This page contains resources about Computational Neuroscience in general. More specific information is included in each subfield. 
Algorithm
This page contains resources about Algorithms and Theory of Computation in general. More specific information is included in each subfield. 
Monte Carlo Method
This page contains resources about Monte Carlo Methods, Sampling Methods, Monte Carlo Inference, Stochastic Simulation, Systems Simulation and Computational Modelling. Subfields and Concepts[edit edit source] Monte Carlo techniques Particle Filtering/ Sequential Monte Carlo (SMC
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