KnowIt: Deep Time Series Modeling and Interpretation
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Abstract (arXiv)
KnowIt (Knowledge discovery in time series data) is a flexible framework for building deep time series models and interpreting them. It is implemented as a Python toolkit, with source code and documentation available from https://must-deep-learning.github.io/KnowIt. It imposes minimal assumptions about task specifications and decouples the definition of dataset, deep neural network architecture, and interpretability technique through well defined interfaces. This ensures the ease of importing new datasets, custom architectures, and the definition of different interpretability paradigms while maintaining on-the-fly modeling and interpretation of different aspects of a user's own time series data. KnowIt aims to provide an environment where users can perform knowledge discovery on their own complex time series data through building powerful deep learning models and explaining their behavior. With ongoing development, collaboration and application our goal is to make this a platform to progress this underexplored field and produce a trusted tool for deep time series modeling.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 23 references that are in the map. First posted on arXiv 8 Jul 2025.
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References · 12
- 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
- 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,447
- 2019Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecastingcited by 748
- 2020Captum: A unified and generic model interpretability library for PyTorchcited by 542
- 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
- 2021Dive into Deep Learningcited by 111
- 2021Darts: User-Friendly Modern Machine Learning for Time Seriescited by 90
- 2021Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Surveycited by 71
- 2019Towards a Rigorous Evaluation of XAI Methods on Time Seriescited by 67
- 2021Merlion: A Machine Learning Library for Time Seriescited by 25
- 2023Decomposing Global Feature Effects Based on Feature Interactionscited by 17
- 2020FlowDB a large scale precipitation, river, and flash flood datasetcited by 7
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