-
Notifications
You must be signed in to change notification settings - Fork 2
Expand file tree
/
Copy pathpaper.bib
More file actions
146 lines (134 loc) · 5.87 KB
/
paper.bib
File metadata and controls
146 lines (134 loc) · 5.87 KB
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
@misc{byambadalai2024estimatingdistributionaltreatmenteffects,
title={Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction},
author={Undral Byambadalai and Tatsushi Oka and Shota Yasui},
year={2024},
eprint={2407.16037},
archivePrefix={arXiv},
primaryClass={econ.EM},
url={https://arxiv.org/abs/2407.16037},
}
@book{fisher1935design,
title={The Design of Experiments},
author={Fisher, Ronald A.},
year={1935},
publisher={Oliver and Boyd}
}
@ARTICLE{2020NumPy-Array,
author = {Harris, Charles R. and Millman, K. Jarrod and
van der Walt, Stéfan J and Gommers, Ralf and
Virtanen, Pauli and Cournapeau, David and
Wieser, Eric and Taylor, Julian and Berg, Sebastian and
Smith, Nathaniel J. and Kern, Robert and Picus, Matti and
Hoyer, Stephan and van Kerkwijk, Marten H. and
Brett, Matthew and Haldane, Allan and
Fernández del Río, Jaime and Wiebe, Mark and
Peterson, Pearu and Gérard-Marchant, Pierre and
Sheppard, Kevin and Reddy, Tyler and Weckesser, Warren and
Abbasi, Hameer and Gohlke, Christoph and
Oliphant, Travis E.},
title = {Array programming with {NumPy}},
journal = {Nature},
year = {2020},
volume = {585},
pages = {357--362},
doi = {10.1038/s41586-020-2649-2}
}
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
journal={Journal of Machine Learning Research},
volume={12},
pages={2825--2830},
year={2011}
}
@inproceedings{byambadalai2025efficientestimationdistributionaltreatment,
title={On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization},
author={Undral Byambadalai and Tomu Hirata and Tatsushi Oka and Shota Yasui},
booktitle={Proceedings of the 42nd International Conference on Machine Learning},
year={2025},
series={ICML'25},
url={https://arxiv.org/abs/2506.05945}
}
@misc{hirata2025efficientscalableestimationdistributional,
title={Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks},
author={Tomu Hirata and Undral Byambadalai and Tatsushi Oka and Shota Yasui and Shunsuke Uto},
year={2025},
eprint={2507.07738},
archivePrefix={arXiv},
primaryClass={econ.EM},
url={https://arxiv.org/abs/2507.07738}
}
@misc{byambadalai2025imperfectcompliance,
title={Beyond the Average: Distributional Causal Inference under Imperfect Compliance},
author={Undral Byambadalai and Tomu Hirata and Tatsushi Oka and Shota Yasui},
year={2025},
eprint={2509.15594},
archivePrefix={arXiv},
primaryClass={econ.EM},
url={https://arxiv.org/abs/2509.15594}
}
@article{dowhy,
title={DoWhy: An End-to-End Library for Causal Inference},
author={Sharma, Amit and Kiciman, Emre},
journal={arXiv preprint arXiv:2011.04216},
year={2020},
url={https://arxiv.org/abs/2011.04216}
}
@inproceedings{econml,
title={Causal Inference and Machine Learning in Practice with {EconML} and {CausalML}: Industrial Use Cases at {Microsoft}, {TripAdvisor}, {Uber}},
author={Battocchi, Keith and Dillon, Eleanor and Hei, Maggie and Lewis, Greg and Ling, Miruna and Rao, Jing and Shyr, Dennis and Syrgkanis, Vasilis},
booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
pages={4072--4073},
year={2021},
organization={ACM}
}
@ARTICLE{2020SciPy-NMeth,
author = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and
Haberland, Matt and Reddy, Tyler and Cournapeau, David and
Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and
Bright, Jonathan and van der Walt, St{\'e}fan J. and
Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and
Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and
Kern, Robert and Larson, Eric and Carey, C J and
Polat, {\.I}lhan and Feng, Yu and Moore, Eric W. and
VanderPlas, Jake and Laxalde, Denis and Perktold, Josef and
Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and
Harris, Charles R. and Archibald, Anne M. and
Ribeiro, Ant{\^o}nio H. and Pedregosa, Fabian and
van Mulbregt, Paul and {SciPy 1.0 Contributors}},
title = {{SciPy} 1.0: Fundamental Algorithms for Scientific Computing in Python},
journal = {Nature Methods},
year = {2020},
volume = {17},
pages = {261--272},
doi = {10.1038/s41592-019-0686-2}
}
@misc{hillstrom2008,
title={The MineThatData E-Mail Analytics And Data Mining Challenge},
author={Hillstrom, Kevin},
year={2008},
url={https://blog.minethatdata.com/2008/03/minethatdata-e-mail-analytics-and-data.html}
}
@article{finkelstein2012,
title={The Oregon Health Insurance Experiment: Evidence from the First Year},
author={Finkelstein, Amy and Taubman, Sarah and Wright, Bill and Bernstein, Mira and Gruber, Jonathan and Newhouse, Joseph P. and Allen, Heidi and Baicker, Katherine and {Oregon Health Study Group}},
journal={The Quarterly Journal of Economics},
volume={127},
number={3},
pages={1057--1106},
year={2012},
doi={10.1093/qje/qjs020}
}
@article{kobrosly2020causalcurve,
title={causal-curve: A Python Causal Inference Package to Estimate Causal Dose-Response Curves},
author={Kobrosly, Roni W.},
journal={Journal of Open Source Software},
volume={5},
number={52},
pages={2523},
year={2020},
doi={10.21105/joss.02523}
}