| High-dimensional consistency in score-based and hybrid structure learning P Nandy, A Hauser, MH Maathuis The Annals of Statistics 46 (6A), 3151-3183, 2018 | 179 | 2018 |
| Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge AL Tarca, M Lauria, M Unger, E Bilal, S Boue, K Kumar Dey, J Hoeng, ... Bioinformatics 29 (22), 2892-2899, 2013 | 134 | 2013 |
| Estimating the effect of joint interventions from observational data in sparse high-dimensional settings P Nandy, MH Maathuis, TS Richardson The Annals of Statistics 45 (2), 647-674, 2017 | 95 | 2017 |
| Robust causal structure learning with some hidden variables B Frot, P Nandy, MH Maathuis Journal of the Royal Statistical Society, Series B: Statistical Methodology …, 2019 | 55 | 2019 |
| A Review of Some Recent Advances in Causal Inference MH Maathuis, P Nandy Handbook of Big Data, 387-407, 2016 | 50 | 2016 |
| Achieving Fairness via Post-Processing in Web-Scale Recommender Systems P Nandy, C Diciccio, D Venugopalan, H Logan, K Basu, NE Karoui arXiv preprint arXiv:2006.11350, 2021 | 44 | 2021 |
| Large-sample theory for the Bergsma-Dassios sign covariance P Nandy, L Weihs, M Drton The Electronic Journal of Statistics 10 (2), 2287-2311, 2016 | 27 | 2016 |
| Structure learning of linear gaussian structural equation models with weak edges MF Eigenmann, P Nandy, MH Maathuis 33rd Conference on Uncertainty in Artificial Intelligence, 2017 | 25 | 2017 |
| A/B Testing in Dense Large-Scale Networks: Design and Inference P Nandy, K Basu, S Chatterjee, Y Tu Advances in Neural Information Processing Systems 34, 2020 | 24 | 2020 |
| Inference for Individual Mediation Effects and Interventional Effects in Sparse High-Dimensional Causal Graphical Models A Chakrabortty, P Nandy, H Li arXiv preprint arXiv:1809.10652, 2018 | 24 | 2018 |
| Pushing the limits of fairness impossibility: Who's the fairest of them all? B Hsu, R Mazumder, P Nandy, K Basu Advances in Neural Information Processing Systems 35, 32749-32761, 2022 | 22 | 2022 |
| Long-term dynamics of fairness intervention in connection recommender systems NJ Akpinar, C DiCiccio, P Nandy, K Basu Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 22-35, 2022 | 18 | 2022 |
| A/B testing for recommender systems in a two-sided marketplace P Nandy, D Venugopalan, C Lo, S Chatterjee Advances in Neural Information Processing Systems 35, 6466-6477, 2021 | 18 | 2021 |
| Personalized Treatment Selection using Causal Heterogeneity Y Tu, K Basu, C DiCiccio, R Bansal, P Nandy, P Jaikumar, S Chatterjee arXiv preprint arXiv:1901.10550, 2020 | 17 | 2020 |
| Optimal convergence for stochastic optimization with multiple expectation constraints K Basu, P Nandy arXiv preprint arXiv:1906.03401, 2019 | 13 | 2019 |
| Optimal variational perturbations for the inference of stochastic reaction dynamics C Zechner, P Nandy, M Unger, H Koeppl 2012 IEEE 51st IEEE conference on decision and control (CDC), 5336-5341, 2012 | 11 | 2012 |
| Package ‘pcalg’ M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ... | 10* | 2024 |
| Offline reinforcement learning for mobile notifications Y Yuan, A Muralidharan, P Nandy, M Cheng, P Prabhakar Proceedings of the 31st ACM International Conference on Information …, 2022 | 10 | 2022 |
| Detection and mitigation of algorithmic bias via predictive parity C DiCiccio, B Hsu, Y Yu, P Nandy, K Basu Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 8 | 2023 |
| pcalg: Methods for graphical models and causal inference M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ... R Package retrieved from https://CRAN. R-project. org/package= pcalg, 2021 | 8 | 2021 |
Heinz KoepplTechnische Universität Darmstadt, Dept. Electrical Engineering and Dept. Biologybcs.tu-darmstadt.de의 이메일 확인됨
