Chao Ma
Chao Ma
Machine Learning Group, Computational and Biological Learning Lab, University of Cambridge
Verified email at - Homepage
Cited by
Cited by
Eddi: Efficient dynamic discovery of high-value information with partial vae
C Ma, S Tschiatschek, K Palla, JM HernŠndez-Lobato, S Nowozin, ...
International Conference on Machine Learning, 2019
Variational implicit processes
C Ma, Y Li, JM HernŠndez-Lobato
International Conference on Machine Learning, 2019
A Lyapunov-type inequality for a fractional differential equation with Hadamard derivative
Q Ma, C Ma, J Wang
Journal of Mathematical Inequalities 11 (1), 135-141, 2017
Partial VAE for hybrid recommender system
C Ma, W Gong, JM HernŠndez-Lobato, N Koenigstein, S Nowozin, ...
NIPS Workshop on Bayesian Deep Learning 2018, 2018
An accurate European option pricing model under Fractional Stable Process based on Feynman Path Integral
C Ma, Q Ma, H Yao, T Hou
Physica A: Statistical Mechanics and its Applications 494, 87-117, 2018
A novel combinational forecasting model of dust storms based on rare classes classification algorithm
Z Zhang, C Ma, J Xu, J Huang, L Li
International Conference on Geo-Informatics in Resource Management and†…, 2014
A Novel Combination Forecast Method on Non-Stationary Time Series and its Application to Exchange Rate Forecasting
Z Zhang, Z Ouyang, C Ma, J Xu, L Li, Q Wen
Int. J. Simulation—Systems, Sci. Technol. 17 (47), 2016
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
C Ma, S Tschiatschek, JM HernŠndez-Lobato, R Turner, C Zhang
arXiv preprint arXiv:2006.11941, 2020
Incentive-punitive risk function with interval valued intuitionistic fuzzy information for outsourced software project risk assessment
Z Zhang, Y Hu, C Ma, J Xu, S Yuan, Z Chen
Journal of Intelligent & Fuzzy Systems 32 (5), 3749-3760, 2017
HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals
C Ma, S Tschiatschek, Y Li, R Turner, JM Hernandez-Lobato, C Zhang
Symposium on Advances in Approximate Bayesian Inference, 1-8, 2020
Black-box Stein divergence minimization for learning latent variable models
C Ma, D Barber
Advances in Approximate Bayesian Inference, NIPS 2017 Workshop 6, 2017
Data retrieval
S Nowozin, C Zhang, N Koenigstein, C Ma, JMH Lobato, G Wenbo
US Patent App. 16/357,321, 2020
Gathering data in a communication system
C Zhang, RSB Nowozin, A Patel, DCM Belgrave, K Palla, A Thieme, ...
US Patent App. 16/443,734, 2020
Bayesian EDDI: Sequential Variable Selection with Bayesian Partial VAE
C Ma, W Gong, S Tschiatschek, S Nowozin, JM HernŠndez-Lobato, ...
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