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autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm
Selecting the step size for the Metropolis-adjusted Langevin algorithm (MALA) is necessary in order to obtain satisfactory performance. …
Miguel Biron-Lattes, Nikola Surjanovic, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté
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autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm
Pigeons.jl: Distributed sampling from intractable distributions
We introduce a software package, Pigeons.jl, that provides a way to leverage distributed computation to obtain samples from complicated …
Nikola Surjanovic, Miguel Biron-Lattes, Paul Tiede, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté
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Pigeons.jl: Distributed sampling from intractable distributions
Local Exchangeability
Exchangeability – in which the distribution of an infinite sequence is invariant to reorderings of its elements – implies …
Trevor Campbell, Saifuddin Syed, Chiao-Yu Yang, Michael I. Jordan, Tamara Broderick
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Local Exchangeability
A Unified Framework for U-Net Design and Analysis
U-Nets are a go-to, state-of-the-art neural architecture across numerous tasks for continuous signals on a square such as images and …
Christopher Williams, Fabian Falck, George Deligiannidis, Chris Holmes, Arnaud Doucet, Saifuddin Syed
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A Unified Framework for U-Net Design and Analysis
Non-reversible parallel tempering: a scalable highly parallel MCMC scheme
Parallel tempering (PT) methods are a popular class of Markov chain Monte Carlo schemes used to sample complex high-dimensional …
Saifuddin Syed, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet
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Non-reversible parallel tempering: a scalable highly parallel MCMC scheme