Elements of information theory
Elements of information theory
Neural Computation
A practical Bayesian framework for backpropagation networks
Neural Computation
A decision-theoretic extension of stochastic complexity and its applications to learning
IEEE Transactions on Information Theory
A note on the applied use of MDL approximations
Neural Computation
Fluctuation-Dissipation Theorem and Models of Learning
Neural Computation
Estimating Entropy Rates with Bayesian Confidence Intervals
Neural Computation
How Many Clusters? An Information-Theoretic Perspective
Neural Computation
Predictability, Complexity, and Learning
Neural Computation
Application of the Fisher-Rao Metric to Structure Detection
Journal of Mathematical Imaging and Vision
Latent features in similarity judgments: A nonparametric bayesian approach
Neural Computation
IEEE Transactions on Signal Processing
The geometry of prior selection
Neurocomputing
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