research
∙
10/12/2021
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling
Normalizing flows have shown great success as general-purpose density es...
share
research
∙
02/04/2020
tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware
Markov chain Monte Carlo (MCMC) is widely regarded as one of the most im...
research
∙
01/22/2020
Joint Distributions for TensorFlow Probability
A central tenet of probabilistic programming is that a model is specifie...
research
∙
11/01/2019
BERT Goes to Law School: Quantifying the Competitive Advantage of Access to Large Legal Corpora in Contract Understanding
Fine-tuning language models, such as BERT, on domain specific corpora ha...
research
∙
06/07/2019
Automatic Reparameterisation of Probabilistic Programs
Probabilistic programming has emerged as a powerful paradigm in statisti...
research
∙
11/15/2018
Effect Handling for Composable Program Transformations in Edward2
Algebraic effects and handlers have emerged in the programming languages...
research
∙
11/05/2018
Simple, Distributed, and Accelerated Probabilistic Programming
We describe a simple, low-level approach for embedding probabilistic pro...
research
∙
11/28/2017
