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Keno Fischer
Keno Fischer
JuliaHub, Inc.
在 juliahub.com 的电子邮件经过验证
标题
引用次数
引用次数
年份
Fashionable modelling with flux
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
arXiv preprint arXiv:1811.01457, 2018
2202018
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
2152019
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
552019
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
412019
Generalized physics-informed learning through language-wide differentiable programming
C Rackauckas, A Edelman, K Fischer, M Innes, E Saba, VB Shah, ...
382021
Automatic full compilation of Julia programs and ML models to cloud TPUs
K Fischer, E Saba
arXiv preprint arXiv:1810.09868, 2018
152018
Fashionable modelling with flux (2018)
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
arXiv preprint arXiv:1811.01457, 1811
141811
A differentiable programming system to bridge machine learning and scientific computing (2019)
M Innes, A Edelman, K Fischer, C Rackauckas, E Saba, VB Shah, ...
arXiv preprint arXiv:1907.07587, 1907
131907
Fashionable modelling with flux. CoRR abs/1811.01457 (2018)
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
arXiv preprint arXiv:1811.01457, 1811
121811
A differentiable programming system to bridge machine learning and scientific computing, arXiv
M Innes, A Edelman, K Fischer, C Rackauckas, E Saba, VB Shah, ...
arXiv preprint arXiv:1907.07587, 2019
112019
Fashionable Modelling with Flux, CoRR, abs/1811.01457
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
61811
CoRR abs/1811.01457 (2018)
M Innes, E Saba, K Fischer, D Gandhi, MC Rudilosso, NM Joy, T Karmali, ...
arXiv preprint arXiv:1811.01457, 0
6
Composable and reusable neural surrogates to predict system response of causal model components
R Anantharaman, A Abdelrehim, F Martinuzzi, S Yalburgi, E Saba, ...
AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM), 2021
52021
A differentiable programming system to bridge machine learning and scientific computing. doi: 10.48550
M Innes, A Edelman, K Fischer, C Rackauckas, E Saba, VB Shah, ...
arXiv, 1907
51907
A differentiable programming system to bridge machine learning and scientific computing. arXiv 2019
M Innes, A Edelman, K Fischer, C Rackauckas, E Saba, VB Shah, ...
arXiv preprint arXiv:1907.07587, 0
5
Julia e Flux: Modernizando o Aprendizado de Máquina
D Gandhi, M Innes, E Saba, K Fischer, V Shah
Computação Brasil, 41-45, 2019
32019
Flux: Julia machine learning library
M Innes, E Saba, K Fischer, D Gandhi, M Concetto Rudilosso, ...
Astrophysics Source Code Library, ascl: 2110.015, 2021
22021
Blind adaptive beamforming of narrowband signals using an uncalibrated antenna-array by machine learning
S Schoenbrod, E Saba, M Bazdresch, S Kelly, T Besard, K Fischer
2022 IEEE International Symposium on Phased Array Systems & Technology (PAST …, 2022
12022
JuliaPy/pyjulia: v0. 6.0
T Arakaki, J Bolewski, M Cranmer, R Deits, K Fischer, SG Johnson, ...
Zenodo, 2022
2022
Cataloging the Visible Universe through Bayesian Inference at Petascale in Julia
K Fischer
2017
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