Markov processes are widely used mathematical models for describing dyna...
Estimating the mutual information from samples from a joint distribution...
Coarse-grained (CG) molecular dynamics enables the study of biological
p...
Learning a common representation space between vision and language allow...
The high temporal resolution of audio and our perceptual sensitivity to ...
We propose a novel Bayesian neural network architecture that can learn
i...
Safely deploying machine learning models to the real world is often a
ch...
The information bottleneck principle provides an information-theoretic m...
Compression of Neural Networks (NN) has become a highly studied topic in...