7 citations · 19 across the 7 of their papers we have counts for
12 papers
TyXe: Pyro-based Bayesian neural nets for Pytorch
Hippolyt Ritter, Theofanis Karaletsos
We introduce TyXe, a Bayesian neural network library built on top of Pytorch and Pyro. Our leading design principle is to cleanly separate architecture, prior, inference and likeli…
Localized Uncertainty Attacks
Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas +3
The susceptibility of deep learning models to adversarial perturbations has stirred renewed attention in adversarial examples resulting in a number of attacks. However, most of the…
Stochastic Aggregation in Graph Neural Networks
Yuanqing Wang, Theofanis Karaletsos
Graph neural networks (GNNs) manifest pathologies including over-smoothing and limited discriminating power as a result of suboptimally expressive aggregating mechanisms. We herein…
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Theofanis Karaletsos, Thang D. Bui
Probabilistic neural networks are typically modeled with independent weight priors, which do not capture weight correlations in the prior and do not provide a parsimonious interfac…
Generalized Hidden Parameter MDPs Transferable Model-based RL in a Handful of Trials
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos
There is broad interest in creating RL agents that can solve many (related) tasks and adapt to new tasks and environments after initial training. Model-based RL leverages learned s…
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference
Xinyu Hu, Paul Szerlip, Theofanis Karaletsos +1
A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties. The main contributions of this paper are (i) A…