forked from geoelements/gns
-
Notifications
You must be signed in to change notification settings - Fork 0
/
references.bib
156 lines (156 loc) · 5.33 KB
/
references.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
@article{battaglia2018relational,
title={Relational inductive biases, deep learning, and graph networks},
author={Battaglia, Peter W and Hamrick, Jessica B and Bapst, Victor and Sanchez-Gonzalez, Alvaro and Zambaldi, Vinicius and Malinowski, Mateusz and Tacchetti, Andrea and Raposo, David and Santoro, Adam and Faulkner, Ryan and others},
journal={arXiv preprint arXiv:1806.01261},
year={2018}
}
@software{Kumar_Graph_Network_Simulator_2022,
author = {Kumar, Krishna and Vantassel, Joseph},
doi = {10.5281/zenodo.6658322},
month = {6},
title = {{Graph Network Simulator: v1.0.1}},
url = {https://github.com/geoelements/gns},
version = {v1.0.1},
year = {2022}
}
@Conference{kumar2022insitu,
author = "Kumar, Krishna and Navratil, Paul and Solis, Andrew and Vantassel, Joseph",
title = "Minority Report: A graph-network oracle for large-scale in situ visualization",
booktitle = "IEEE Large-Scale Data Analysis and Visualization",
year = "2022",
month = "October",
address = "Oklahoma, USA",
publisher = "IEEE",
}
@inproceedings{sanchez2020learning,
title={Learning to simulate complex physics with graph networks},
author={Sanchez-Gonzalez, Alvaro and Godwin, Jonathan and Pfaff, Tobias and Ying, Rex and Leskovec, Jure and Battaglia, Peter},
booktitle={International Conference on Machine Learning},
pages={8459--8468},
year={2020},
url={https://dl.acm.org/doi/10.5555/3524938.3525722},
organization={PMLR}
}
@article{scarselli2008graph,
title={The graph neural network model},
author={Scarselli, Franco and Gori, Marco and Tsoi, Ah Chung and Hagenbuchner, Markus and Monfardini, Gabriele},
journal={IEEE transactions on neural networks},
volume={20},
number={1},
pages={61--80},
year={2008},
publisher={IEEE}
}
@inproceedings{gilmer2017neural,
title={Neural Message Passing for Quantum Chemistry},
author={Gilmer, Justin and Schoenholz, Samuel S and Riley, Patrick F and Vinyals, Oriol and Dahl, George E},
booktitle={International Conference on Machine Learning},
pages={1263--1272},
year={2017},
organization={PMLR},
}
@article{wu2020comprehensive,
title={A comprehensive survey on graph neural networks},
author={Wu, Zonghan and Pan, Shirui and Chen, Fengwen and Long, Guodong and Zhang, Chengqi and Philip, S Yu},
journal={IEEE Transactions on Neural Networks and Learning Systems},
year={2020},
publisher={IEEE}
}
@article{velivckovic2017graph,
title={Graph attention networks},
author={Veli{\v{c}}kovi{\'c}, Petar and Cucurull, Guillem and Casanova, Arantxa and Romero, Adriana and Lio, Pietro and Bengio, Yoshua},
journal={arXiv preprint arXiv:1710.10903},
year={2017}
}
@article{prume2022model,
title={Model-Free Data-Driven Inference in Computational Mechanics},
author={Prume, Erik and Reese, Stefanie and Ortiz, Michael},
journal={arXiv preprint arXiv:2207.06419},
doi={10.1016/j.cma.2022.115704},
year={2022}
}
@software{vantassel2022gnsdata,
author = {Vantassel, Joseph and Kumar, Krishna},
doi = {10.17603/ds2-0phb-dg64},
month = {10},
title = {{Graph Network Simulator Datasets}},
url = {https://doi.org/10.17603/ds2-0phb-dg64},
version = {v1},
year = {2022}
}
@article{hu2019difftaichi,
title={Difftaichi: Differentiable programming for physical simulation},
author={Hu, Yuanming and Anderson, Luke and Li, Tzu-Mao and Sun, Qi and Carr, Nathan and Ragan-Kelley, Jonathan and Durand, Fr{\'e}do},
journal={arXiv preprint arXiv:1910.00935},
year={2019}
}
@misc{tensorflow2015whitepaper,
title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={https://www.tensorflow.org/},
note={Software available from tensorflow.org},
author={
Mart\'{i}n~Abadi and
Ashish~Agarwal and
Paul~Barham and
Eugene~Brevdo and
Zhifeng~Chen and
Craig~Citro and
Greg~S.~Corrado and
Andy~Davis and
Jeffrey~Dean and
Matthieu~Devin and
Sanjay~Ghemawat and
Ian~Goodfellow and
Andrew~Harp and
Geoffrey~Irving and
Michael~Isard and
Yangqing Jia and
Rafal~Jozefowicz and
Lukasz~Kaiser and
Manjunath~Kudlur and
Josh~Levenberg and
Dandelion~Man\'{e} and
Rajat~Monga and
Sherry~Moore and
Derek~Murray and
Chris~Olah and
Mike~Schuster and
Jonathon~Shlens and
Benoit~Steiner and
Ilya~Sutskever and
Kunal~Talwar and
Paul~Tucker and
Vincent~Vanhoucke and
Vijay~Vasudevan and
Fernanda~Vi\'{e}gas and
Oriol~Vinyals and
Pete~Warden and
Martin~Wattenberg and
Martin~Wicke and
Yuan~Yu and
Xiaoqiang~Zheng},
year={2015},
}
@article{soga2016,
author = {Soga, K. and Alonso, E. and Yerro, A. and Kumar, K. and Bandara, S.},
title = {Trends in large-deformation analysis of landslide mass movements with particular emphasis on the material point method},
journal = {Géotechnique},
volume = {66},
number = {3},
pages = {248-273},
ISSN = {0016-8505
1751-7656},
DOI = {10.1680/jgeot.15.LM.005},
year = {2016}
}
@article{hu2018mlsmpmcpic,
title={A Moving Least Squares Material Point Method with Displacement Discontinuity and Two-Way Rigid Body Coupling},
author={Hu, Yuanming and Fang, Yu and Ge, Ziheng and Qu, Ziyin and Zhu, Yixin and Pradhana, Andre and Jiang, Chenfanfu},
journal={ACM Transactions on Graphics (TOG)},
volume={37},
number={4},
pages={150},
year={2018},
doi={10.1145/3197517.3201293},
publisher={ACM}
}