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aahlad puli
aahlad puli
PhD student, CS, NYU
Verified email at nyu.edu - Homepage
Title
Cited by
Cited by
Year
Removing hidden confounding by experimental grounding
N Kallus, AM Puli, U Shalit
Advances in neural information processing systems 31, 2018
1592018
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
A Puli, LH Zhang, EK Oermann, R Ranganath
ICLR 2022, arXiv preprint arXiv:2107.00520, 2021
55*2021
X-cal: Explicit calibration for survival analysis
M Goldstein, X Han, A Puli, A Perotte, R Ranganath
Advances in neural information processing systems 33, 18296-18307, 2020
442020
General control functions for causal effect estimation from ivs
A Puli, R Ranganath
Advances in neural information processing systems 33, 8440-8451, 2020
23*2020
Don’t blame dataset shift! shortcut learning due to gradients and cross entropy
AM Puli, L Zhang, Y Wald, R Ranganath
Advances in Neural Information Processing Systems 36, 2023
212023
When more is less: Incorporating additional datasets can hurt performance by introducing spurious correlations
R Compton, L Zhang, A Puli, R Ranganath
Machine Learning for Healthcare Conference, 110-127, 2023
172023
Nuisances via negativa: Adjusting for spurious correlations via data augmentation
A Puli, N Joshi, Y Wald, H He, R Ranganath
TMLR 2024, arXiv preprint arXiv:2210.01302, 2022
142022
Inverse-Weighted Survival Games
M Goldstein, X Han, A Puli, T Wies, A Perotte, R Ranganath
NeurIPS (cit. on p. 60), 2021
14*2021
Causal Estimation with Functional Confounders
A Puli, AJ Perotte, R Ranganath
Advances in neural information processing systems 33, 5115, 2020
112020
Beyond distribution shift: Spurious features through the lens of training dynamics
N Murali, A Puli, K Yu, R Ranganath, K Batmanghelich
Transactions on machine learning research 2023, https://openreview. net …, 2023
8*2023
Learning invariant representations with missing data
M Goldstein, JH Jacobsen, O Chau, A Saporta, AM Puli, R Ranganath, ...
Conference on Causal Learning and Reasoning, 290-301, 2022
82022
Individual treatment effect estimation in the presence of unobserved confounding using proxies: a cohort study in stage III non-small cell lung cancer
WAC van Amsterdam, JJC Verhoeff, NI Harlianto, GA Bartholomeus, ...
Scientific reports 12 (1), 5848, 2022
82022
Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning
Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, SD Maidman, ...
European Heart Journal: Acute Cardiovascular Care 13 (6), 472-480, 2024
72024
Contra: Contrarian statistics for controlled variable selection
M Sudarshan, A Puli, L Subramanian, S Sankararaman, R Ranganath
International conference on artificial intelligence and statistics, 1900-1908, 2021
42021
DIET: Conditional independence testing with marginal dependence measures of residual information
M Sudarshan, A Puli, W Tansey, R Ranganath
International Conference on Artificial Intelligence and Statistics, 10343-10367, 2023
32023
New-onset diabetes assessment using artificial intelligence-enhanced electrocardiography
N Jethani, A Puli, H Zhang, L Garber, L Jankelson, Y Aphinyanaphongs, ...
arXiv preprint arXiv:2205.02900, 2022
32022
Robust anomaly detection for particle physics using multi-background representation learning
A Gandrakota, LH Zhang, A Puli, K Cranmer, J Ngadiuba, R Ranganath, ...
Machine Learning: Science and Technology 5 (3), 035082, 2024
22024
Bayesian Modeling of Marketing Attribution
R Sinha, D Arbour, AM Puli
arXiv preprint arXiv:2205.15965, 2022
22022
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
A Saporta, AM Puli, M Goldstein, R Ranganath
Advances in Neural Information Processing Systems 37, 56919-56957, 2024
12024
A dynamic risk score for early prediction of cardiogenic shock using machine learning
Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, S Maidman, ...
arXiv preprint arXiv:2303.12888, 2023
12023
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Articles 1–20