In this talk, I will introduce hinge-loss Markov random fields (HLMRFs), a new kind of probabilistic graphical model that supports scalable collective inference from richly structured data. HL-MRFs unify three different

Source URL: mmds-data.org

A Bayesian model for identifying hierarchically organised states in neural population activity Patrick Putzky1,2,3 , Florian Franzen1,2,3 , Giacomo Bassetto1,3 , Jakob H. Macke1,3 1 Max Planck Institute for Biological Cy

Source URL: www.mackelab.org

• Computational neuroscience
• Statistics
• Neuroscience
• Statistical theory
• Neural networks
• Bioinformatics
• Artificial neural network
• Bayesian network
• Neural coding
• Variational Bayesian methods
• Bayesian inference
• Hidden Markov model

Scalable Computing: Practice and Experience Scientific International Journal for Parallel and Distributed Computing ISSN:

Source URL: www.scpe.org

• Engineering
• Computing
• Theoretical computer science
• Product testing
• Systems engineering
• Workflow technology
• Model checkers
• PRISM model checker
• Model checking
• Workflow
• Markov chain
• Reliability engineering

Interactive HMM construction based on interesting sequences Szymon Jaroszewicz National Institute of Telecommunications Warsaw, Poland

Source URL: www.ke.tu-darmstadt.de

• Markov models
• Machine learning
• Probability
• Statistics
• Bioinformatics
• Computational linguistics
• Hidden Markov model
• Markov chain
• BaumWelch algorithm
• Speech recognition
• Expectationmaximization algorithm
• Association rule learning

Adaptive Discriminative Generative Model and Its Applications † Ruei-Sung Lin† David Ross‡ Jongwoo Lim† Ming-Hsuan Yang∗ University of Illinois ‡ University of Toronto ∗ Honda Research Institute

Source URL: www.cs.toronto.edu

• Statistics
• Probability
• Mathematical analysis
• Statistical models
• Machine learning
• Markov models
• Linear algebra
• Multivariate statistics
• Discriminative model
• Kalman filter
• Generative model
• Normal distribution

Hidden Markov Models Markov Models Hidden Markov Models

Source URL: cl.indiana.edu

• Markov models
• Probability theory
• Machine learning
• Probability
• Hidden Markov model
• Speech recognition
• Markov chain
• BaumWelch algorithm

September 14, :56 WSPC - Proceedings Trim Size: 9.75in x 6.5in

Source URL: www.jsbi.org

• Bioinformatics
• Computational phylogenetics
• Biology
• Mathematical and theoretical biology
• HMMER
• Sequence alignment
• BLAST
• Sequence analysis
• FASTA
• Hidden Markov model
• SmithWaterman algorithm
• Homology modeling

A Short Introduction to Probabilistic Soft Logic Angelika Kimmig1,2 , Stephen H. Bach1 , Matthias Broecheler3 , Bert Huang1 , Lise Getoor1 1 University of Maryland, 2 KU Leuven, 3 Aurelius LLC

Source URL: stephenbach.net

• Logic
• Philosophy
• Abstraction
• Bayesian statistics
• Markov networks
• Reasoning
• Model theory
• Semantics
• Probabilistic soft logic
• Markov logic network
• Probabilistic logic
• Statistical relational learning

Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

Source URL: www.cs.huji.ac.il

• Bayesian statistics
• Statistics
• Graphical models
• Probability
• Markov models
• Bayesian network
• Probability distribution
• Markov chain
• Expectation propagation
• Approximate inference
• Likelihood function
• Hidden Markov model

STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES R. C. van Dalen, J. Yang, H. Wang, A. Ragni, C. Zhang, M. J. F. Gales Department of Engineering, University of Cambridge, United Kingdom In this paper,

Source URL: mi.eng.cam.ac.uk

• Markov models
• Machine learning
• Artificial intelligence
• Learning
• Computational linguistics
• Speech recognition software
• Computer accessibility
• Speech recognition
• Hidden Markov model
• Conditional random field
• Language model
• Image segmentation