Dave Moore

Publication Activity (10 Years)

Years Active: 2009-2022
Publications (10 Years): 13

Top Topics

Probabilistic Modeling

Conditional Distributions

Competitive Advantage

Top Venues

Publications

Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. ICLR (2022)
Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. CoRR (2021)
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven
Automatic structured variational inference. AISTATS (2021)
Junpeng Lao, Christopher Suter, Ian Langmore, Cyril Chimisov, Ashish Saxena, Pavel Sountsov, Dave Moore, Rif A. Saurous, Matthew D. Hoffman, Joshua V. Dillon
tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware. CoRR (2020)
Dan Piponi, Dave Moore, Joshua V. Dillon
Joint Distributions for TensorFlow Probability. CoRR (2020)
Maria I. Gorinova, Dave Moore, Matthew D. Hoffman
Automatic Reparameterisation of Probabilistic Programs. ICML (2020)
Maria I. Gorinova, Dave Moore, Matthew D. Hoffman
Automatic Reparameterisation of Probabilistic Programs. CoRR (2019)
Emad Elwany, Dave Moore, Gaurav Oberoi
BERT Goes to Law School: Quantifying the Competitive Advantage of Access to Large Legal Corpora in Contract Understanding. CoRR (2019)
Dustin Tran, Matthew D. Hoffman, Dave Moore, Christopher Suter, Srinivas Vasudevan, Alexey Radul
Simple, Distributed, and Accelerated Probabilistic Programming. NeurIPS (2018)
Dave Moore, Maria I. Gorinova
Effect Handling for Composable Program Transformations in Edward2. CoRR (2018)
Dustin Tran, Matthew D. Hoffman, Dave Moore, Christopher Suter, Srinivas Vasudevan, Alexey Radul, Matthew J. Johnson, Rif A. Saurous
Simple, Distributed, and Accelerated Probabilistic Programming. CoRR (2018)
Tongzhou Wang, Yi Wu, Dave Moore, Stuart J. Russell
Meta-Learning MCMC Proposals. NeurIPS (2018)
Joshua V. Dillon, Ian Langmore, Dustin Tran, Eugene Brevdo, Srinivas Vasudevan, Dave Moore, Brian Patton, Alex Alemi, Matthew D. Hoffman, Rif A. Saurous
TensorFlow Distributions. CoRR (2017)
Dave Moore, Tim Barnard
With Eloquence and Humanity? Human Factors/Ergonomics in Sustainable Human Development. Hum. Factors 54 (6) (2012)
Zöe Handley, Mike Sharples, Dave Moore
Training novel phonemic contrasts: a comparison of identification and oddity discrimination training. SLaTE (2009)