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08/16/2023
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series
Learning directed acyclic graphs (DAGs) to identify causal relations und...
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06/25/2023
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
Learning Granger causality from event sequences is a challenging but ess...
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05/25/2023
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization
Domain generalization (DG) is a prevalent problem in real-world applicat...
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05/10/2023
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences
Learning causal structure among event types from discrete-time event seq...
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05/07/2022
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance
Domain adaptation on time-series data is often encountered in the indust...
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11/30/2021
gCastle: A Python Toolbox for Causal Discovery
is an end-to-end Python toolbox for causal structure learning. It provi...
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05/23/2021
THP: Topological Hawkes Processes for Learning Granger Causality on Event Sequences
Learning Granger causality among event types on multi-type event sequenc...
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05/07/2021
An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks
Alarm root cause analysis is a significant component in the day-to-day t...
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12/22/2020
Time Series Domain Adaptation via Sparse Associative Structure Alignment
Domain adaptation on time series data is an important but challenging ta...
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11/04/2020
Mixed Set Domain Adaptation
In the settings of conventional domain adaptation, categories of the sou...
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06/28/2019
