1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen +1
In supervised learning, understanding an input's proximity to the training data can help a model decide whether it has sufficient evidence for reaching a reliable prediction. While…
Self-Reflective Variational Autoencoder
Ifigeneia Apostolopoulou, Elan Rosenfeld, Artur Dubrawski
The Variational Autoencoder (VAE) is a powerful framework for learning probabilistic latent variable generative models. However, typical assumptions on the approximate posterior di…
Tractable Learning and Inference for Large-Scale Probabilistic Boolean Networks
Ifigeneia Apostolopoulou, Diana Marculescu
Probabilistic Boolean Networks (PBNs) have been previously proposed so as to gain insights into complex dy- namical systems. However, identification of large networks and of the un…