Towards plausibility in time series counterfactual explanations | ScienceToStartup | ScienceToStartup

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References (27)

[1]

OptunaHub: A Platform for Black-Box Optimization

2025Yoshihiko Ozaki, Shuhei Watanabe et al.

[2]

No $D_{train}$: Model-Agnostic Counterfactual Explanations Using Reinforcement Learning

2025Xiangyu Sun, Raquel Aoki et al.

[3]

M-CELS: Counterfactual Explanation for Multivariate Time Series Data Guided by Learned Saliency Maps

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"Generate plausible counterfactual explanations for time series classification using gradient-based optimization and soft-DTW alignment, enabling more realistic temporal structure."

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Towards plausibility in time series counterfactual explanations

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References (27)

Founder's Pitch

"Generate plausible counterfactual explanations for time series classification using gradient-based optimization and soft-DTW alignment, enabling more realistic temporal structure."

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Towards plausibility in time series counterfactual explanations

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References (27)

Founder's Pitch

"Generate plausible counterfactual explanations for time series classification using gradient-based optimization and soft-DTW alignment, enabling more realistic temporal structure."

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