9.7k citations · 9.8k across the 3 of their papers we have counts for
3 papers
Dynamic Control Flow in Large-Scale Machine Learning
Yuan Yu, Martín Abadi, Paul Barham +12
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcem…
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi, Ashish Agarwal, Paul Barham +37
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…
CT-NOR: Representing and Reasoning About Events in Continuous Time
Aleksandr Simma, Moises Goldszmidt, John MacCormick +4
We present a generative model for representing and reasoning about the relationships among events in continuous time. We apply the model to the domain of networked and distributed…