Researching causal relationships in time series data using Temporal Convolutional Networks (TCNs) combined with attention mechanisms. This approach aims to identify complex temporal interactions. Additionally, we're incorporating uncertainty quantification to enhance the reliability of our causal predictions.
machine-learning causality attention-mechanism causality-analysis time-series-analysis causal-discovery deep-learrning temporal-causal-discovery
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Updated
Jun 14, 2024 - Jupyter Notebook