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Austin Goddard
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2020 – today
- 2024
- [c5]Austin Goddard, Kang Du, Yu Xiang:
Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification. ISIT 2024: 190-195 - [i4]Austin Goddard, Kang Du, Yu Xiang:
Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification. CoRR abs/2404.15245 (2024) - 2023
- [c4]Austin Goddard, Yu Xiang, Ilya Soloveychik:
Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels. ACSSC 2023: 932-936 - [i3]Austin Goddard, Yu Xiang, Ilya Soloveychik:
Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels. CoRR abs/2308.10119 (2023) - 2022
- [c3]Austin Goddard, Yu Xiang, Ilya Soloveychik:
Lower Bounds on the Error Probability for Invariant Causal Prediction. MLSP 2022: 1-6 - [i2]Austin Goddard, Yu Xiang, Ilya Soloveychik:
Lower Bounds on the Error Probability for Invariant Causal Prediction. CoRR abs/2206.14362 (2022) - 2021
- [c2]Austin Goddard, Yu Xiang:
A Subsampling-Based Method for Causal Discovery on Discrete Data. SSP 2021: 341-345 - [i1]Austin Goddard, Yu Xiang:
A Subsampling-Based Method for Causal Discovery on Discrete Data. CoRR abs/2108.13984 (2021) - 2020
- [c1]Kang Du, Austin Goddard, Yu Xiang:
On the Robustness of Causal Discovery with Additive Noise Models on Discrete Data. DCC 2020: 365
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last updated on 2024-10-13 18:00 CEST by the dblp team
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