Kai Xu / 徐锴
Kai Xu / 徐锴
Research Scientist, MIT-IBM Watson AI Lab
Verified email at - Homepage
Cited by
Cited by
Turing: a language for flexible probabilistic inference
H Ge, K Xu, Z Ghahramani
International conference on artificial intelligence and statistics, 1682-1690, 2018
Telescoping Density-Ratio Estimation
B Rhodes, K Xu, MU Gutmann
Advances in Neural Information Processing Systems 33, 2020
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
Interpreting Deep Classifier by Visual Distillation of Dark Knowledge
K Xu, DH Park, C Yi, C Sutton
arXiv preprint arXiv:1803.04042, 2018
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
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
Variational Russian Roulette for Deep Bayesian Nonparametrics
K Xu, A Srivastava, C Sutton
International Conference on Machine Learning, 6963-6972, 2019
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
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
Couplings for Multinomial Hamiltonian Monte Carlo
K Xu, TE Fjelde, C Sutton, H Ge
International Conference on Artificial Intelligence and Statistics, 2021
Generative Ratio Matching Networks
A Srivastava, K Xu, MU Gutmann, C Sutton
Eighth International Conference on Learning Representations, 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
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
dpart: Differentially private autoregressive tabular, a general framework for synthetic data generation
S Mahiou, K Xu, G Ganev
arXiv preprint arXiv:2207.05810, 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
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
Understanding how Differentially Private Generative Models Spend their Privacy Budget
G Ganev, K Xu, E De Cristofaro
arXiv preprint arXiv:2305.10994, 2023
Improving the reconstruction of disentangled representation learners via multi-stage modelling
A Srivastava, Y Bansal, Y Ding, C Hurwitz, K Xu, B Egger, P Sattigeri, ...
arXiv preprint arXiv:2010.13187, 2020
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
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
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