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Found 3 papers, 1 papers with code
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference
As an alternative, we propose SMC-Wake, a procedure for fitting an amortized variational approximation that uses likelihood-tempered sequential Monte Carlo samplers to estimate the gradient of the inclusive KL divergence.
Amortized Variational Inference with Coverage Guarantees
We prove lower bounds on the predictive efficiency of the regions produced by CANVI and explore how the quality of a posterior approximation relates to the predictive efficiency of prediction regions based on that approximation.
Linear-time inference for Gaussian Processes on one dimension
Gaussian Processes (GPs) provide powerful probabilistic frameworks for interpolation, forecasting, and smoothing, but have been hampered by computational scaling issues.
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