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Jamie Smith

3 accepted papers

2023

Score-Based Diffusion Models as Principled Priors for Inverse Imaging

ICCV 2023poster

Priors are essential for reconstructing images from noisy and/or incomplete measurements. The choice of the prior determines both the quality and uncertainty of recovered images. We propose turning score-based diffusion models into principled image priors ("score-based priors") for analyzing a poste…

Cited by 85PDFScholar
2021

Variational Data Assimilation with a Learned Inverse Observation Operator

ICML 2021spotlight

Variational data assimilation optimizes for an initial state of a dynamical system such that its evolution fits observational data. The physical model can subsequently be evolved into the future to make predictions. This principle is a cornerstone of large scale forecasting applications such as nume…

2018

Learning Memory Access Patterns

ICML 2018oral

The explosion in workload complexity and the recent slow-down in Moore’s law scaling call for new approaches towards efficient computing. Researchers are now beginning to use recent advances in machine learning in software optimizations; augmenting or replacing traditional heuristics and data struct…

Cited by 278SourcePDFScholar