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Identification of Partially Observed Causal Models: Graphical Conditions for the Linear Non-Gaussian and Heterogeneous Cases - Adams, Hansen, Zhang 2021
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Learning latent causal graphs via mixture oracles - Kivva, Rajendran, Ravikumar, and Aragam 2021
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Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA - Lachapelle, Rodríguez López, Sharma, Everett, Le Priol, Lacoste, Lacoste-Julien
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Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model - Lee, Nagabandi, Abbeel, Levine
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Learning Latent Dynamics for Planning from Pixels - Hafner, Lillicrap, Fischer, Villegas, Ha, Lee, Davidson
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Learning Latent Causal Dynamics - Yao, Chen, and Zhang, 2022
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Structure by Architecture: Disentangled Representations without Regularization - Leeb, Lanzillotta, Annadani, Besserve, Bauer, Schölkopf, 2020
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CITRIS: Causal Identifiability from Temporal Intervened Sequences - Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves