Chao Ma

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Data Imputation

Causal Inference

Missing Data Imputation

Top Venues

Publications

Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Shuyu Liu, Ting Chen, Tiantian Zhao, Shanshan Liu, Chao Ma
Research on cooperative UAV countermeasure strategy based on interception triangle. ICMLCA (2023)
Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. ICLR (2023)
Ruibo Tu, Chao Ma, Cheng Zhang
Causal-Discovery Performance of ChatGPT in the context of Neuropathic Pain Diagnosis. CoRR (2023)
Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo. NeurIPS (2022)
Weijie He, Xiaohao Mao, Chao Ma, Yu Huang, José Miguel Hernández-Lobato, Ting Chen
BSODA: A Bipartite Scalable Framework for Online Disease Diagnosis. WWW (2022)
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. CoRR (2022)
Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo. CoRR (2022)
Chao Ma, Cheng Zhang
Identifiable Generative models for Missing Not at Random Data Imputation. NeurIPS (2021)
Chao Ma, José Miguel Hernández-Lobato
Functional Variational Inference based on Stochastic Process Generators. NeurIPS (2021)
Chao Ma, Cheng Zhang
Identifiable Generative Models for Missing Not at Random Data Imputation. CoRR (2021)
Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. NeurIPS (2020)
Chao Ma, Sebastian Tschiatschek, José Miguel Hernández-Lobato, Richard E. Turner, Cheng Zhang
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. CoRR (2020)
Weijie He, Xiaohao Mao, Chao Ma, José Miguel Hernández-Lobato, Ting Chen
FIT: a Fast and Accurate Framework for Solving Medical Inquiring and Diagnosing Tasks. CoRR (2020)
Chao Ma, Yingzhen Li, José Miguel Hernández-Lobato
Variational Implicit Processes. ICML (2019)
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. ICML (2019)
Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals. AABI (2019)
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. CoRR (2018)
Chao Ma, Yingzhen Li, José Miguel Hernández-Lobato
Variational Implicit Processes. CoRR (2018)