164 citations · 236 across the 5 of their papers we have counts for
3 papers · 1 filter
Scalable Spatiotemporal Prediction with Bayesian Neural Fields
Feras Saad, Jacob Burnim, Colin Carroll +4
Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-de…
Online Normalization for Training Neural Networks
Vitaliy Chiley, Ilya Sharapov, Atli Kosson +5
Online Normalization is a new technique for normalizing the hidden activations of a neural network. Like Batch Normalization, it normalizes the sample dimension. While Online Norma…
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Urs Köster, Tristan J. Webb, Xin Wang +11
Deep neural networks are commonly developed and trained in 32-bit floating point format. Significant gains in performance and energy efficiency could be realized by training and in…