7 citations · 7 across the 3 of their papers we have counts for
3 papers
Robust and integrative Bayesian neural networks for likelihood-free parameter inference
Fredrik Wrede, Robin Eriksson, Richard Jiang +4
State-of-the-art neural network-based methods for learning summary statistics have delivered promising results for simulation-based likelihood-free parameter inference. Existing ap…
Scalable Bayesian Functional Connectivity Inference for Multi-Electrode Array Recordings
Yun Zhao, Richard Jiang, Zhenni Xu +3
Multi-electrode arrays (MEAs) can record extracellular action potentials (also known as 'spikes') from hundreds or thousands of neurons simultaneously. Inference of a functional ne…
Bayesian Inference over the Stiefel Manifold via the Givens Representation
Arya A Pourzanjani, Richard M Jiang, Brian Mitchell +2
We introduce an approach based on the Givens representation for posterior inference in statistical models with orthogonal matrix parameters, such as factor models and probabilistic…