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On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization
Causal discovery from observational data is an important but challenging...
06/05/2021 ∙ by Ruichu Cai, et al. ∙
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THP: Topological Hawkes Processes for Learning Granger Causality on Event Sequences
Learning Granger causality among event types on multi-type event sequenc...
05/23/2021 ∙ by Ruichu Cai, et al. ∙
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Learning Disentangled Semantic Representation for Domain Adaptation
Domain adaptation is an important but challenging task. Most of the exis...
12/22/2020 ∙ by Ruichu Cai, et al. ∙
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DeepACC:Automate Chromosome Classification based on Metaphase Images using Deep Learning Framework Fused with Prior Knowledge
Chromosome classification is an important but difficult and tedious task...
06/28/2020 ∙ by Chunlong Luo, et al. ∙
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Disentanglement Challenge: From Regularization to Reconstruction
The challenge of learning disentangled representation has recently attra...
11/30/2019 ∙ by Jie Qiao, et al. ∙
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Causal Discovery with Cascade Nonlinear Additive Noise Models
Identification of causal direction between a causal-effect pair from obs...
05/23/2019 ∙ by Ruichu Cai, et al. ∙
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