14 citations · 29 across the 10 of their papers we have counts for
4 papers · 1 filter
When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate
Florent Forest, Amaury Wei, Olga Fink
Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series. It appears in many domains, including healthcare, f…
Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers
Chi-Ching Hsu, Gaëtan Frusque, Florent Forest +3
Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds.…
Interpretable Prognostics with Concept Bottleneck Models
Florent Forest, Katharina Rombach, Olga Fink
Deep learning approaches have recently been extensively explored for the prognostics of industrial assets. However, they still suffer from a lack of interpretability, which hinders…
Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis
Florent Forest, Olga Fink
Intelligent Fault Diagnosis (IFD) based on deep learning has proven to be an effective and flexible solution, attracting extensive research. Deep neural networks can learn rich rep…