| Predicting enhancer‐promoter interaction from genomic sequence with deep neural networks S Singh, Y Yang, B Póczos, J Ma Quantitative Biology 7 (2), 122-137, 2019 | 145* | 2019 |
| Interpretable sequence learning for COVID-19 forecasting SO Arik, CL Li, J Yoon, R Sinha, A Epshteyn, LT Le, V Menon, S Singh, ... Advances in Neural Information Processing Systems, 2020 | 102 | 2020 |
| Finite-sample analysis of fixed-k nearest neighbor density functional estimators S Singh, B Póczos Advances in Neural Information Processing Systems, 1217-1225, 2016 | 97* | 2016 |
| Exploiting sequence-based features for predicting enhancer–promoter interactions Y Yang, R Zhang, S Singh, J Ma Bioinformatics 33 (14), i252-i260, 2017 | 96 | 2017 |
| Nonparametric density estimation under adversarial losses S Singh, A Uppal, B Li, CL Li, M Zaheer, B Póczos Advances in Neural Information Processing Systems 31, 2018 | 79 | 2018 |
| Minimax distribution estimation in Wasserstein distance S Singh, B Póczos arXiv preprint arXiv:1802.08855, 2018 | 73 | 2018 |
| Nonparametric density estimation & convergence rates for GANs under Besov IPM losses A Uppal, S Singh, B Póczos Advances in Neural Information Processing Systems, 9089-9100, 2019 | 70 | 2019 |
| Generalized exponential concentration inequality for Rényi divergence estimation S Singh, B Póczos International Conference on Machine Learning, 333-341, 2014 | 64 | 2014 |
| Exponential Concentration of a Density Functional Estimator S Singh, B Poczos Advances in Neural Information Processing Systems (NIPS), 3032-3040, 2014 | 54 | 2014 |
| Probable domain generalization via quantile risk minimization C Eastwood, A Robey, S Singh, J Von Kügelgen, H Hassani, GJ Pappas, ... Neural Information Processing Systems (NeurIPS), 2022 | 44 | 2022 |
| A hidden Markov model for analyzing eye-tracking of moving objects J Kim, S Singh, ED Thiessen, AV Fisher Behavior Research Methods, 1-19, 2020 | 33 | 2020 |
| Adjustment in tumbling rates improves bacterial chemotaxis on obstacle-laden terrains S Rashid, Z Long, S Singh, M Kohram, H Vashistha, S Navlakha, ... Proceedings of the National Academy of Sciences 116 (24), 11770-11775, 2019 | 22 | 2019 |
| Nonparanormal Information Estimation S Singh, B Poczos arXiv preprint arXiv:1702.07803, 2017 | 21 | 2017 |
| A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan SÖ Arık, J Shor, R Sinha, J Yoon, JR Ledsam, LT Le, MW Dusenberry, ... NPJ digital medicine 4 (1), 146, 2021 | 20 | 2021 |
| Optimal Binary Classification Beyond Accuracy S Singh, JT Khim Advances in Neural Information Processing Systems 35, 18226-18240, 2022 | 11* | 2022 |
| Continuum-armed bandits: A function space perspective S Singh International Conference on Artificial Intelligence and Statistics, 2620-2628, 2021 | 11 | 2021 |
| Distributed Gradient Descent in Bacterial Food Search S Singh, S Rashid, Z Long, S Navlakha, H Salman, ZN Oltvai, ... Annual International Conference on Research in Computational Molecular Biology, 2016 | 11 | 2016 |
| Darc: Differentiable architecture compression S Singh, A Khetan, Z Karnin arXiv preprint arXiv:1905.08170, 2019 | 9 | 2019 |
| Minimax reconstruction risk of convolutional sparse dictionary learning S Singh, B Póczos, J Ma International Conference on Artificial Intelligence and Statistics, 1327-1336, 2018 | 6 | 2018 |
| Spuriosity didn’t kill the classifier: Using invariant predictions to harness spurious features C Eastwood, S Singh, AL Nicolicioiu, M Vlastelica Pogančić, ... Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
Barnabas PoczosAssociate professor, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
