| On the (in) fidelity and sensitivity of explanations CK Yeh, CY Hsieh, A Suggala, DI Inouye, PK Ravikumar Advances in Neural Information Processing Systems 32, 2019 | 338 | 2019 |
| Comparing Twitter Summarization Algorithms for Multiple Post Summaries DI Inouye, JK Kalita IEEE International Conference on Social Computing (SocialCom), 2011 | 247 | 2011 |
| A review of multivariate distributions for count data derived from the Poisson distribution DI Inouye, E Yang, GI Allen, P Ravikumar Wiley Interdisciplinary Reviews: Computational Statistics 9 (3), e1398, 2017 | 132 | 2017 |
| Summarization of twitter microblogs BP Sharifi, DI Inouye, JK Kalita The computer journal 57 (3), 378-402, 2014 | 60 | 2014 |
| Admixture of Poisson MRFs: A topic model with word dependencies DI Inouye, P Ravikumar, I Dhillon Proceedings of The 31st International Conference on Machine Learning (ICML …, 2014 | 40 | 2014 |
| Shapley Explanation Networks R Wang, X Wang, DI Inouye International Conference on Learning Representations (ICLR), 2021 | 30 | 2021 |
| Multiple post microblog summarization DI Inouye REU Research Final Report 1, 34-40, 2010 | 30 | 2010 |
| Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies DI Inouye, P Ravikumar, IS Dhillon Proceedings of the 33rd International Conference on Machine Learning (ICML), 2016 | 26 | 2016 |
| Towards undistorted and noise-free speech in an MRI scanner: correlation subtraction followed by spectral noise gating JM Inouye, SS Blemker, DI Inouye The Journal of the Acoustical Society of America 135 (3), 1019-1022, 2014 | 18 | 2014 |
| Feature shift detection: Localizing which features have shifted via conditional distribution tests S Kulinski, S Bagchi, DI Inouye Advances in Neural Information Processing Systems (NeurIPS), 2020 | 16 | 2020 |
| Deep Density Destructors DI Inouye, P Ravikumar International Conference on Machine Learning, 2172-2180, 2018 | 16 | 2018 |
| Hyperparameter Selection under Localized Label Noise via Corrupt Validation DI Inouye, P Ravikumar, P Das, A Datta Learning with Limited Labeled Data NeurIPS Workshop, 2017 | 10 | 2017 |
| Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs DI Inouye, PK Ravikumar, IS Dhillon Advances in Neural Information Processing Systems (NIPS), 3158-3166, 2014 | 10 | 2014 |
| Styleuv: Diverse and high-fidelity uv map generative model M Lee, W Cho, M Kim, D Inouye, N Kwak arXiv preprint arXiv:2011.12893, 2020 | 9 | 2020 |
| Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial DI Inouye, PK Ravikumar, IS Dhillon Advances in Neural Information Processing Systems (NIPS), 3213-3221, 2015 | 8 | 2015 |
| VisIRR: Interactive visual information retrieval and recommendation for large-scale document data J Choo, C Lee, E Clarkson, Z Liu, H Lee, DHP Chau, F Li, R Kannan, ... Georgia Institute of Technology, 2013 | 8 | 2013 |
| Automated Dependence Plots DI Inouye, L Leqi, JS Kim, B Aragam, P Ravikumar Uncertainty in Artificial Intelligence (UAI), 2020 | 6* | 2020 |
| Towards explaining distribution shifts S Kulinski, DI Inouye International Conference on Machine Learning, 17931-17952, 2023 | 5 | 2023 |
| Iterative alignment flows Z Zhou, Z Gong, P Ravikumar, DI Inouye International Conference on Artificial Intelligence and Statistics, 6409-6444, 2022 | 4* | 2022 |
| Efficient federated domain translation Z Zhou, SS Azam, C Brinton, DI Inouye The Eleventh International Conference on Learning Representations, 2022 | 3 | 2022 |
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
