Results 1 to 10 of about 93,812 (304)
Impact of local adaptation measures and regional climate change on perceived temperature
Meteorologische Zeitschrift, 2013 The perceived temperature (PT) is a measure for the quantification of human thermal comfort developed by the German Meteorological Service (DWD). In the present article, the sensitivity of PT on air temperature, water vapour pressure, wind speed, mean ...
Robert Schoetter +5 more
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Automatic Differentiation Variational Inference
CoRR, 2016 Probabilistic modeling is iterative. A scientist posits a simple model, fits it to her data, refines it according to her analysis, and repeats. However, fitting complex models to large data is a bottleneck in this process. Deriving algorithms for new models can be both mathematically and computationally challenging, which makes it difficult to ...
Alp Kucukelbir +4 more
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Galois Slicing as Automatic Differentiation
CoRRGalois slicing is a technique for program slicing for provenance, developed by Perera and collaborators. Galois slicing aims to explain program executions by demonstrating how to track approximations of the input and output forwards and backwards along a particular execution.
Robert Atkey, Roly Perera
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Ionospheric Radio Beacon Signal Analysis and Parameter Estimation Using Automatic Differentiation
Journal of Geophysical Research: Machine Learning and ComputationContinuous wave signals from a network of high frequency (HF) beacons in Peru and other instruments are used to reconstruct the regional ionospheric electron number density in the volume surrounding the network. The continuous wave (CW) HF signals employ
Jhassmin A. Aricoche, David L. Hysell
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A Source Identification Problem in Magnetics Solved by Means of Deep Learning Methods
MathematicsIn this study, a deep learning-based approach is used to address inverse problems involving the inversion of a magnetic field and the identification of the relevant source, given the field data within a specific subdomain.
Sami Barmada +4 more
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DiffSharp: Automatic Differentiation Library
CoRR, 2015 5 pages, 1 figure, minor fixes, added ...
Atilim Gunes Baydin +2 more
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Machine Learning: Science and TechnologyParameter estimation using observables is a fundamental concept in the experimental sciences. Mathematical models that represent the physical processes can enable reconstructions of the experimental observables and greatly assist in parameter estimation ...
A L Milder +3 more
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Staging Automatic Differentiation with Fusion
Proceedings of the 18th ACM SIGPLAN International Haskell Symposiumsponsorship: We would like to thank the reviewers for their constructive feedback and suggestions. Part of this work was funded by the Flemish Fund for Scientific Research (FWO): project G0A9423N. (Flemish Fund for Scientific Research (FWO)|G0A9423N)
Klumpers, Samuel, Schrijvers, Tom
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows
Journal of Geophysical Research: Machine Learning and ComputationFull waveform inversion (FWI) is able to construct high‐resolution subsurface models by iteratively minimizing discrepancies between observed and simulated seismic data.
Feng Liu +3 more
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Automatic Differentiation is no Panacea for Phylogenetic Gradient Computation. [PDF]
Genome Biol Evol, 2023 Fourment M +6 more
europepmc +1 more source