| Turing: a language for flexible probabilistic inference H Ge, K Xu, Z Ghahramani International conference on artificial intelligence and statistics, 1682-1690, 2018 | 455* | 2018 |
| Telescoping Density-Ratio Estimation B Rhodes, K Xu, MU Gutmann Advances in Neural Information Processing Systems 33, 2020 | 108 | 2020 |
| Interpreting Deep Classifier by Visual Distillation of Dark Knowledge K Xu, DH Park, C Yi, C Sutton arXiv preprint arXiv:1803.04042, 2018 | 40 | 2018 |
| AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms K Xu, H Ge, W Tebbutt, M Tarek, M Trapp, Z Ghahramani Symposium on Advances in Approximate Bayesian Inference, 1-10, 2020 | 38* | 2020 |
| Targeted Neural Dynamical Modeling C Hurwitz, A Srivastava, K Xu, J Jude, M Perich, L Miller, M Hennig Advances in Neural Information Processing Systems 34, 29379-29392, 2021 | 34 | 2021 |
| A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics K Xu, A Srivastava, D Gutfreund, F Sosa, T Ullman, J Tenenbaum, ... Advances in Neural Information Processing Systems 34, 2478-2490, 2021 | 26 | 2021 |
| SpectraGAN: Spectrum based generation of city scale spatiotemporal mobile network traffic data K Xu, R Singh, M Fiore, MK Marina, H Bilen, M Usama, H Benn, ... Proceedings of the 17th International Conference on emerging Networking …, 2021 | 23 | 2021 |
| Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference CL Hurwitz, K Xu, A Srivastava, AP Buccino, M Hennig Advances in Neural Information Processing Systems 32, 4726-4738, 2019 | 20 | 2019 |
| Variational Russian Roulette for Deep Bayesian Nonparametrics K Xu, A Srivastava, C Sutton International Conference on Machine Learning, 6963-6972, 2019 | 19 | 2019 |
| Couplings for Multinomial Hamiltonian Monte Carlo K Xu, TE Fjelde, C Sutton, H Ge International Conference on Artificial Intelligence and Statistics, 2021 | 15 | 2021 |
| Generative Ratio Matching Networks A Srivastava, K Xu, MU Gutmann, C Sutton Eighth International Conference on Learning Representations, 2019 | 14* | 2019 |
| Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression A Srivastava, S Han, K Xu, B Rhodes, MU Gutmann Transactions on Machine Learning Research, 2023 | 12 | 2023 |
| dpart: Differentially private autoregressive tabular, a general framework for synthetic data generation S Mahiou, K Xu, G Ganev arXiv preprint arXiv:2207.05810, 2022 | 10 | 2022 |
| CartaGenie: Context-driven synthesis of city-scale mobile network traffic snapshots K Xu, R Singh, H Bilen, M Fiore, MK Marina, Y Wang 2022 IEEE International Conference on Pervasive Computing and Communications …, 2022 | 10 | 2022 |
| DynamicPPL: Stan-like speed for dynamic probabilistic models M Tarek, K Xu, M Trapp, H Ge, Z Ghahramani arXiv preprint arXiv:2002.02702, 2020 | 10 | 2020 |
| Bijectors.jl: Flexible transformations for probability distributions TE Fjelde, K Xu, M Tarek, S Yalburgi, H Ge The Second Symposium on Advances in Approximate Bayesian Inference, 2019 | 6 | 2019 |
| Understanding how Differentially Private Generative Models Spend their Privacy Budget G Ganev, K Xu, E De Cristofaro arXiv preprint arXiv:2305.10994, 2023 | 5 | 2023 |
| Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation K Xu, G Ganev, E Joubert, R Davison, O Van Acker, L Robinson The Eleventh International Conference on Learning Representations, 2023 | 5 | 2023 |
| Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modeling A Srivastava, Y Bansal, Y Ding, CL Hurwitz, K Xu, B Egger, P Sattigeri, ... arXiv preprint arXiv:2010.13187, 2020 | 5 | 2020 |
| Gendt: mobile network drive testing made efficient with generative modeling C Sun, K Xu, MK Marina, H Benn Proceedings of the 18th International Conference on emerging Networking …, 2022 | 3 | 2022 |
Hong GeCambridge UniversityVerified email at cam.ac.uk
