38 citations · 110 across the 9 of their papers we have counts for
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cs.LG2022★ 10 cited
Representational dissimilarity metric spaces for stochastic neural networks
Lyndon R. Duong, Jingyang Zhou, Josue Nassar +3
Quantifying similarity between neural representations -- e.g. hidden layer activation vectors -- is a perennial problem in deep learning and neuroscience research. Existing methods…
stat.ML2022
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture Models
Yixin Wang, Anthony Degleris, Alex H. Williams +1
Neyman-Scott processes (NSPs) are point process models that generate clusters of points in time or space. They are natural models for a wide range of phenomena, ranging from neural…