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07/25/2023
Continuous Time Evidential Distributions for Irregular Time Series
Prevalent in many real-world settings such as healthcare, irregular time...
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06/03/2023
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
Interpreting time series models is uniquely challenging because it requi...
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04/07/2023
Interpretable Unified Language Checking
Despite recent concerns about undesirable behaviors generated by large l...
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02/08/2023
Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks
Irregularly-sampled time series (ITS) are native to high-impact domains ...
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11/20/2022
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Large pre-trained models decay over long-term deployment as input distri...
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10/11/2022
Class-Specific Explainability for Deep Time Series Classifiers
Explainability helps users trust deep learning solutions for time series...
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08/21/2022
Stop Hop: Early Classification of Irregular Time Series
Early classification algorithms help users react faster to their machine...
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05/22/2022
TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks
Foodborne illness is a serious but preventable public health problem – w...
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05/06/2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Machine learning models in safety-critical settings like healthcare are ...
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03/17/2022
