On the Robustness of Causal Discovery with Additive Noise Models on Discrete Data. - Kang Du; Austin Goddard; Yu Xiang 004 (DCC, 2020)

A Subsampling-Based Method for Causal Discovery on Discrete Data. - Austin Goddard; Yu Xiang 004 (SSP, 2021)

Lower Bounds on the Error Probability for Invariant Causal Prediction. - Austin Goddard; Yu Xiang 004; Ilya Soloveychik (MLSP, 2022)

Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels. - Austin Goddard; Yu Xiang 004; Ilya Soloveychik (ACSSC, 2023)

Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification. - Austin Goddard; Kang Du; Yu Xiang 004 (ISIT, 2024)