Keno Fischer
Keno Fischer
Julia Computing, Inc.
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A differentiable programming system to bridge machine learning and scientific computing
M Innes, A Edelman, K Fischer, C Rackauckas, E Saba, VB Shah, ...
arXiv preprint arXiv:1907.07587, 2019
Fashionable modelling with flux
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
arXiv preprint arXiv:1811.01457, 2018
Cataloging the visible universe through Bayesian inference in Julia at petascale
J Regier, K Fischer, K Pamnany, A Noack, J Revels, M Lam, S Howard, ...
Journal of Parallel and Distributed Computing 127, 89-104, 2019
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
L Yang, S Treichler, T Kurth, K Fischer, D Barajas-Solano, J Romero, ...
2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS), 1-11, 2019
Generalized physics-informed learning through language-wide differentiable programming
C Rackauckas, A Edelman, K Fischer, M Innes, E Saba, VB Shah, ...
Automatic full compilation of Julia programs and ML models to cloud TPUs
K Fischer, E Saba
arXiv preprint arXiv:1810.09868, 2018
Flux: Julia machine learning library
M Innes, E Saba, K Fischer, D Gandhi, M Concetto Rudilosso, ...
Astrophysics Source Code Library, ascl: 2110.015, 2021
Composable and Reusable Neural Surrogates to Predict System Response of Causal Model Components
R Anantharaman, A Abdelrehim, F Martinuzzi, S Yalburgi, K Fischer, ...
AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM), 2021
Yin, Junqi 84 Zhang, Zhao 45, 69
C Adams, AA Awan, D Barajas-Solano, JK Bassett, D Bhowmik, T Bicer, ...
LLVM-HPC’14 Program Committee Members
C Carruth, S Shende, T Grosser, G Funck, R Karrenberg, N Rotem, A Trick, ...
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