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36 Results
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Poster
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Wed 12:00 |
Automatic Reparameterisation of Probabilistic Programs Maria Gorinova · Dave Moore · Matthew Hoffman |
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Poster
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Thu 14:00 |
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models Aytunc Sahin · Yatao Bian · Joachim Buhmann · Andreas Krause |
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Poster
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Thu 6:00 |
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics Matthew Hoffman · Yian Ma |
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Poster
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Wed 8:00 |
Stochastic Gradient and Langevin Processes Xiang Cheng · Dong Yin · Peter Bartlett · Michael Jordan |
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Poster
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Wed 10:00 |
Handling the Positive-Definite Constraint in the Bayesian Learning Rule Wu Lin · Mark Schmidt · Mohammad Emtiyaz Khan |
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Poster
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Tue 13:00 |
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans · Volodimir Begy · Gilles Louppe |
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Poster
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Thu 13:00 |
Kernel interpolation with continuous volume sampling Ayoub Belhadji · Rémi Bardenet · Pierre Chainais |
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Poster
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Thu 7:00 |
Variational Inference for Sequential Data with Future Likelihood Estimates Geon-Hyeong Kim · Youngsoo Jang · Hongseok Yang · Kee-Eung Kim |
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Poster
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Wed 12:00 |
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Yuan Zhou · Hongseok Yang · Yee-Whye Teh · Tom Rainforth |
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Poster
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Tue 7:00 |
Faster Graph Embeddings via Coarsening Matthew Fahrbach · Gramoz Goranci · Richard Peng · Sushant Sachdeva · Chi Wang |
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Poster
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Tue 12:00 |
On Contrastive Learning for Likelihood-free Inference Conor Durkan · Iain Murray · George Papamakarios |
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Poster
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Tue 9:00 |
How Good is the Bayes Posterior in Deep Neural Networks Really? Florian Wenzel · Kevin Roth · Bastiaan Veeling · Jakub Swiatkowski · Linh Tran · Stephan Mandt · Jasper Snoek · Tim Salimans · Rodolphe Jenatton · Sebastian Nowozin |