substructure
DebiasingGraphNeuralNetworksviaLearning DisentangledCausalSubstructure
With the disentangled representations, we synthesize the counterfactual unbiased training samples to further decorrelate causal and bias variables.
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Curvature Filtrations for Graph Generative Model Evaluation Joshua Southern
This state of the art was recently critiqued by O'Bray et al.
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Discrete Object Generation with Reversible Inductive Construction
Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams
Neural Information Processing Systems http://nips.cc/
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
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