1 code implementation • 4 May 2022 • Adalberto Claudio Quiros, Nicolas Coudray, Anna Yeaton, Xinyu Yang, Bojing Liu, Hortense Le, Luis Chiriboga, Afreen Karimkhan, Navneet Narula, David A. Moore, Christopher Y. Park, Harvey Pass, Andre L. Moreira, John Le Quesne, Aristotelis Tsirigos, Ke Yuan
Definitive cancer diagnosis and management depend upon the extraction of information from microscopy images by pathologists.
no code implementations • NeurIPS 2018 • Tongzhou Wang, Yi Wu, David A. Moore, Stuart J. Russell
The learned neural proposals generalize to occurrences of common structural motifs across different models, allowing for the construction of a library of learned inference primitives that can accelerate inference on unseen models with no model-specific training required.
no code implementations • 2 Mar 2017 • David A. Moore, Stuart J. Russell
Detecting weak seismic events from noisy sensors is a difficult perceptual task.
no code implementations • 2 Dec 2016 • Jun Song, David A. Moore
We introduce a novel approach for parallelizing MCMC inference in models with spatially determined conditional independence relationships, for which existing techniques exploiting graphical model structure are not applicable.
1 code implementation • NeurIPS 2015 • David A. Moore, Stuart J. Russell
Gaussian processes have been successful in both supervised and unsupervised machine learning tasks, but their computational complexity has constrained practical applications.