| Composable effects for flexible and accelerated probabilistic programming in NumPyro D Phan, N Pradhan, M Jankowiak arXiv preprint arXiv:1912.11554, 2019 | 270* | 2019 |
| Data analytic approach for bankruptcy prediction H Son, C Hyun, D Phan, HJ Hwang Expert Systems with Applications 138, 112816, 2019 | 125 | 2019 |
| Plex: Towards reliability using pretrained large model extensions D Tran, J Liu, MW Dusenberry, D Phan, M Collier, J Ren, K Han, Z Wang, ... arXiv preprint arXiv:2207.07411, 2022 | 89 | 2022 |
| Functional tensors for probabilistic programming F Obermeyer, E Bingham, M Jankowiak, D Phan, JP Chen arXiv preprint arXiv:1910.10775, 2019 | 19 | 2019 |
| Endpoint temperature prediction model for LD converters using machine-learning techniques H Jo, HJ Hwang, D Phan, Y Lee, H Jang 2019 IEEE 6th International Conference on Industrial Engineering and …, 2019 | 18 | 2019 |
| Surrogate likelihoods for variational annealed importance sampling M Jankowiak, D Phan International Conference on Machine Learning, 9881-9901, 2022 | 12 | 2022 |
| On uncertainty calibration and selective generation in probabilistic neural summarization: A benchmark study P Zablotskaia, D Phan, J Maynez, S Narayan, J Ren, J Liu arXiv preprint arXiv:2304.08653, 2023 | 8 | 2023 |
| On the Fokker–Planck equations with inflow boundary conditions HJ Hwang, D Phan Quarterly of Applied Mathematics 75 (2), 287-308, 2017 | 5 | 2017 |
| Training Chain-of-Thought via Latent-Variable Inference D Phan, MD Hoffman, D Dohan, S Douglas, TA Le, AT Parisi, P Sountsov, ... Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 3* | 2023 |
| Iterative NUTS, May 2019 D Phan, N Pradhan URL https://github.com/pyro-ppl/numpyro/wiki/Iterative-NUTS, 0 | 3 | |
| On Compositional Uncertainty Quantification for Seq2seq Graph Parsing Z Lin, D Phan, P Pasupat, JZ Liu, J Shang The Eleventh International Conference on Learning Representations, 2022 | 1 | 2022 |
| Reparameterized Variational Rejection Sampling M Jankowiak, D Phan stat 1050, 26, 2023 | | 2023 |
| Machine Learning Technology applied to Steel Manufacturing Process H JO, S HWANG, D PHAN, HJ HWANG | | |
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