Journal ArticleDOI
Pattern Recognition and Machine Learning
TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
Citations
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BookDOI
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference
TL;DR: This work presents a reformulation of the stochastic optimal control problem in terms of KL divergence minimisation, not only providing a unifying perspective of previous approaches in this area, but also demonstrating that the formalism leads to novel practical approaches to the control problem.
Journal ArticleDOI
Artificial intelligence (AI) methods in optical networks: A comprehensive survey
Javier Mata,Ignacio de Miguel,Ramón J. Durán,Noemí Merayo,Sandeep Singh,Admela Jukan,Mohit Chamania +6 more
TL;DR: A comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks and a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.
Journal ArticleDOI
Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data
Fernando Amat,William C. Lemon,Daniel P. Mossing,Katie McDole,Yinan Wan,Kristin Branson,Eugene W. Myers,Philipp J. Keller +7 more
TL;DR: This work presents an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed, and performs the first cell lineage reconstruction of early Drosophila melanogaster nervous system development.
Journal ArticleDOI
Build, Compute, Critique, Repeat: Data Analysis with Latent Variable Models
TL;DR: This work describes probabilistic graphical models, a language for formulating latent variable models, and describes mean field variational inference, a generic algorithm for approximating conditional distributions.
Journal ArticleDOI
A phd Filter for Tracking Multiple Extended Targets Using Random Matrices
Karl Granstrom,Umut Orguner +1 more
TL;DR: This paper presents a random set based approach to tracking of an unknown number of extended targets, in the presence of clutter measurements and missed detections, where the targets' extensions are modeled as random matrices, resulting in the Gaussian inverse Wishart phd (giw-phd) filter.