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Dave Moore

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Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling

Oct 17, 2021
Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni

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tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware

Feb 04, 2020
Junpeng Lao, Christopher Suter, Ian Langmore, Cyril Chimisov, Ashish Saxena, Pavel Sountsov, Dave Moore, Rif A. Saurous, Matthew D. Hoffman, Joshua V. Dillon

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Joint Distributions for TensorFlow Probability

Jan 22, 2020
Dan Piponi, Dave Moore, Joshua V. Dillon

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BERT Goes to Law School: Quantifying the Competitive Advantage of Access to Large Legal Corpora in Contract Understanding

Nov 01, 2019
Emad Elwany, Dave Moore, Gaurav Oberoi

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Automatic Reparameterisation of Probabilistic Programs

Jun 07, 2019
Maria I. Gorinova, Dave Moore, Matthew D. Hoffman

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Simple, Distributed, and Accelerated Probabilistic Programming

Nov 29, 2018
Dustin Tran, Matthew Hoffman, Dave Moore, Christopher Suter, Srinivas Vasudevan, Alexey Radul, Matthew Johnson, Rif A. Saurous

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Effect Handling for Composable Program Transformations in Edward2

Nov 15, 2018
Dave Moore, Maria I. Gorinova

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TensorFlow Distributions

Nov 28, 2017
Joshua V. Dillon, Ian Langmore, Dustin Tran, Eugene Brevdo, Srinivas Vasudevan, Dave Moore, Brian Patton, Alex Alemi, Matt Hoffman, Rif A. Saurous

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