SANDIA Reports
Reports Optimization Strategies for Complex Engineering Applications Dakota Software Training Optimization Efficient and Robust Gradient Enhanced Kriging Emulators
Websites
Alex Minnaar : Deep Learning Basics: Neural Networks, Backpropagation and Stochastic Gradient Descent Neural Networks – A Systematic Introduction – Raul Rojas Neural Networks and Deep Learning – Michael Nielsen UFLDL Tutorial
Website
UFLDL Tutorial: Deepa Learning Tutorial DeepLearning 0.1 documentation DeepLearning 0.1 : Contents Artificial neural network Types of artificial neural network Deep learning Multilayer perceptrons Sigmoid function Generalised logistic function Logistic regression Softmax function Multiple kernel learning Sparse matrix Rectifier (Neural Network) Generalized additive model Additive Model Backfitting algorithm A Complete Tutorial on Tree Based Modeling … Read more
Gaussian Process & Genetic Algorithm
Optimization of Gaussian Process Models with Evolutionary Algorithms A genetic Gaussian process regression model based on memetic algorithm Accelerating Evolutionary Algorithms with Gaussian Process Fitness Function Models The Use of Genetic Algorithms for Searching Parameter Space in Gaussian Process Modeling GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm A COMPARISON BETWEEN GAUSSIAN PROCESS EMULATION … Read more
Roberto Calandra
List Publications
Deep Learning for Reinforcement Learning in Pacman
Bachelor-Thesis von Aaron Hochländer aus Wiesbaden
Efficient Reinforcement Learning using Gaussian Processes
Marc Peter Deisenroth