87 citations · 104 across the 3 of their papers we have counts for
4 papers
Benchmarking Deep Learning Interpretability in Time Series Predictions
Aya Abdelsalam Ismail, Mohamed Gunady, Héctor Corrada Bravo +1
Saliency methods are used extensively to highlight the importance of input features in model predictions. These methods are mostly used in vision and language tasks, and their appl…
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks
Aya Abdelsalam Ismail, Mohamed Gunady, Luiz Pessoa +2
Recent efforts to improve the interpretability of deep neural networks use saliency to characterize the importance of input features to predictions made by models. Work on interpre…
Improving Long-Horizon Forecasts with Expectation-Biased LSTM Networks
Aya Abdelsalam Ismail, Timothy Wood, Héctor Corrada Bravo
State-of-the-art forecasting methods using Recurrent Neural Net- works (RNN) based on Long-Short Term Memory (LSTM) cells have shown exceptional performance targeting short-horizon…
Anomaly Classification with the Anti-Profile Support Vector Machine
Wikum Dinalankara, Hector Corrada Bravo
We introduce the anti-profile Support Vector Machine (apSVM) as a novel algorithm to address the anomaly classification problem, an extension of anomaly detection where the goal is…