Mapping Uncertainty With Differentiable Programming
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In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course. 2022 LLVM Developers' Meeting ------ LAGrad: Leveraging the MLIR Ecosystem for Efficient ... Talk at the Applied Category Theory 2020 Conference Main website: More talks in this playlist: ... Deep learning has led to encouraging successes in many challenging tasks. However, a deep neural model lacks interpretability ... Jan Drgona, Pacific Northwest National Laboratory July 10, 2024 Fourth Symposium on Machine Learning and Dynamical ... This tutorial will cover how to optimise various aspects of analyses -- such as cuts, binning, and learned observables like neural ...
Talk from HSF/IRIS-HEP Analysis Ecosystem 2 Workshop ( e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large ...
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Last Updated: June 12, 2026
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