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This paper proposes a Disentangled gEnerative cAusal Representation (DEAR) learning method under appropriate supervised information.
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Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 2019
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Causality for machine learning
Bernhard Schölkopf · 2019
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Robustly disentangled causal mechanisms: Validating deep representations for interventional robustness
Raphael Suter, Djordje Miladinovic, Bernhard Schölkopf, and Stefan Bauer · 2019
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Dag-gnn: Dag structure learning with graph neural networks
Yue Yu, Jie Chen, Tian Gao, and Mo Yu · 2019
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Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2019
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