171 citations · 937 across the 54 of their papers we have counts for
4 papers · 1 filter
Bayesian inference via rejection filtering
Nathan Wiebe, Christopher Granade, Ashish Kapoor +1
We provide a method for approximating Bayesian inference using rejection sampling. We not only make the process efficient, but also dramatically reduce the memory required relative…
Safe Control under Uncertainty
Dorsa Sadigh, Ashish Kapoor
Controller synthesis for hybrid systems that satisfy temporal specifications expressing various system properties is a challenging problem that has drawn the attention of many rese…
Quantum Inspired Training for Boltzmann Machines
Nathan Wiebe, Ashish Kapoor, Christopher Granade +1
We present an efficient classical algorithm for training deep Boltzmann machines (DBMs) that uses rejection sampling in concert with variational approximations to estimate the grad…
Inferring and Learning from Neuronal Correspondences
Ashish Kapoor, E. Paxon Frady, Stefanie Jegelka +2
We introduce and study methods for inferring and learning from correspondences among neurons. The approach enables alignment of data from distinct multiunit studies of nervous syst…