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Found 5 papers, 0 papers with code
An Automatic Operation Batching Strategy for the Backward Propagation of Neural Networks Having Dynamic Computation Graphs
These strategies, however, will miss some important opportunities to group the operations in the backward propagation of training neural networks.
On Data Imbalance in Molecular Property Prediction with Pre-training
In this study, we propose an effective pre-training method that addresses the imbalance in input data.
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?
In material science, the prediction of unobserved values, commonly referred to as extrapolation, is particularly critical for property prediction as it enables researchers to gain insight into materials beyond the limits of available data.
mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks.
Automatic Graph Partitioning for Very Large-scale Deep Learning
RaNNC also achieved better training throughputs than GPipe on both the enlarged BERT model pre-training (GPipe with hybrid parallelism) and the enlarged ResNet models (GPipe with model parallelism) in all of the settings we tried.
