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Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization
Learning causal representation from multi-instance bags significantly improves performances of both MIL and OOD tasks.
Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang
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Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization
Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference
Inferencing causality using data from Australia’s largest cultural heritage crowdsourcing platform reveals that the spontaneous …
Xuanhui Zhang, Weijia Zhang, Yuxiang (Chris) Zhao, Qinghua Zhu
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Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference
Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels using Variational Auto-Encoder
A deep generative approach for non-i.i.d multi-instance learning.
Weijia Zhang
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Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels using Variational Auto-Encoder
Mining heterogeneous causal effects for personalized cancer treatment
A method for estimating heterogeneous treatment effects from survival data.
Weijia Zhang, Thuc Duy Le, Lin Liu, Zhi-Hua Zhou, Jiuyong Li
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Mining heterogeneous causal effects for personalized cancer treatment