Fetching the paper…
Reading the bibliography…
Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations.
C. Ahdida et al. (SHiP), (2019), 10.1088/1748-0221/14/11/P11028 , arXiv:1909.04451 [physics.ins-det]
1909
Earlier work this paper cites.
D. Belayneh et al. , (2019), 10.1140/epjc/s10052-020-8251-9 , arXiv:1912.06794 [physics.ins-det]
1912
Earlier work this paper cites.
G. Parisi, Nucl. Phys. B 180
1981
Earlier work this paper cites.
P. E. Kloeden and E. Platen, in Numerical Solution of Stochastic Differential Equations (Springer, 1992) pp. 103–160
1992
Earlier work this paper cites.
U. Grenander and M. I. Miller, Journal of the royal statistical society series b-methodological 56
1994
Earlier work this paper cites.
S. Agostinelli et al. , Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 506
2003
Earlier work this paper cites.
J. Song, C. Meng, and S. Ermon, CoRR abs/2010.02502
2010
Earlier work this paper cites.
2011
Earlier work this paper cites.
D. P. Kingma and M. Welling, arXiv e-prints , arXiv:1312.6114 (2013) , arXiv:1312.6114 [stat.ML]
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
D. Rezende and S. Mohamed, in Proceedings of the 32nd International Conference on Machine Learning , Proceedings of Machine Learning Research, Vol. 37, edited by F. Bach and D. Blei (PMLR, Lille, France, 2015) pp. 1530–1538
2015
Earlier work this paper cites.
O. Ronneberger, P. Fischer, and T. Brox, in International Conference on Medical image computing and computer-assisted intervention (Springer, 2015) pp. 234–241
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, in Proceedings of the IEEE conference on computer vision and pattern recognition (2016) pp. 770–778
2016
Earlier work this paper cites.
I. Loshchilov and F. Hutter, CoRR abs/1608.03983
2016
Earlier work this paper cites.
M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard, et al. , in OSDI , Vol. 16 (2016) pp. 265–283
2016
Earlier work this paper cites.
P. Ramachandran, B. Zoph, and Q. V. Le, arXiv preprint arXiv:1710.05941 (2017)
2017
Cited alongside, same era.
F. Chollet, “Keras,” https://github.com/fchollet/keras (2017)
2017
Cited alongside, same era.
L. de Oliveira, M. Paganini, and B. Nachman, J. Phys. Conf. Ser. 1085
2018
Cited alongside, same era.
M. Erdmann, L. Geiger, J. Glombitza, and D. Schmidt, Comput. Softw. Big Sci. 2
2018
Cited alongside, same era.
2018
Cited alongside, same era.
(2022), arXiv:2210.06204 [hep-ex]
2022
Later among the works it cites.
G. Aad et al. (ATLAS), Comput. Softw. Big Sci. 6
2022
Later among the works it cites.
C. Krause, I. Pang, and D. Shih, (2022), arXiv:2210.14245 [physics.ins-det]
2022
Later among the works it cites.
2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
F. Carminati, A. Gheata, G. Khattak, P. Mendez Lorenzo, S. Sharan, and S. Vallecorsa, Proceedings, 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017): Seattle, WA, USA, August 21-25, 2017 1085
2018
Cited alongside, same era.
S. Vallecorsa, Proceedings, 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017): Seattle, WA, USA, August 21-25, 2017 1085
2018
Cited alongside, same era.
P. Musella and F. Pandolfi, Comput. Softw. Big Sci. 2
2018
Cited alongside, same era.
ATL-SOFT-PUB-2018-001 (2018)
2018
Cited alongside, same era.
A. Sergeev and M. D. Balso, arXiv preprint arXiv:1802.05799 (2018)
2018
Cited alongside, same era.
M. Erdmann, J. Glombitza, and T. Quast, Comput. Softw. Big Sci. 3
2019
Cited alongside, same era.
S. Vallecorsa, F. Carminati, and G. Khattak, Proceedings, 23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018): Sofia, Bulgaria, July 9-13, 2018 214
2019
Cited alongside, same era.
2022
Later among the works it cites.
“Fast calorimeter simulation challenge 2022,”
2022
Later among the works it cites.
T. Salimans and J. Ho, in International Conference on Learning Representations (2022)
2022
Later among the works it cites.
M. Faucci Giannelli, G. Kasieczka, C. Krause, B. Nachman, D. Salamani, D. Shih, and A. Zaborowska, “Fast Calorimeter Simulation Challenge 2022 - Dataset 3,” (2022a)
2022
Later among the works it cites.
M. F. Giannelli, G. Kasieczka, C. Krause, B. Nachman, D. Salamani, D. Shih, and A. Zaborowska, “Fast Calorimeter Simulation Challenge 2022 - Dataset 1,” (2022)
2022
Later among the works it cites.
M. Faucci Giannelli, G. Kasieczka, C. Krause, B. Nachman, D. Salamani, D. Shih, and A. Zaborowska, “Fast Calorimeter Simulation Challenge 2022 - Dataset 2,” (2022b)
2022
Later among the works it cites.
M. R. Buckley, C. Krause, I. Pang, and D. Shih, (2023), arXiv:2305.11934 [physics.ins-det]
2023
Closest in time.
J. Liu, A. Ghosh, D. Smith, P. Baldi, and D. Whiteson, (2023), arXiv:2305.11531 [physics.ins-det]
2023
Closest in time.
2023
Closest in time.