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Found 6 papers, 3 papers with code
Grid-Based Decimation for Wavelet Transforms with Stably Invertible Implementation
The constant center frequency to bandwidth ratio (Q-factor) of wavelet transforms provides a very natural representation for audio data.
A Differential Entropy Estimator for Training Neural Networks
Mutual Information (MI) has been widely used as a loss regularizer for training neural networks.
Modelling the Utility of Group Testing for Public Health Surveillance
Although group testing can help to significantly increase testing capabilities, the (repeated) testing of entire populations can exceed the resources of any country.
On the Estimation of Information Measures of Continuous Distributions
In particular, we provide confidence bounds for simple histogram based estimation of differential entropy from a fixed number of samples, assuming that the probability density function is Lipschitz continuous with known Lipschitz constant and known, bounded support.
Minimal Achievable Sufficient Statistic Learning
We introduce Minimal Achievable Sufficient Statistic (MASS) Learning, a training method for machine learning models that attempts to produce minimal sufficient statistics with respect to a class of functions (e. g. deep networks) being optimized over.
