Search Results for author: Héctor Corrada Bravo

Found 3 papers, 2 papers with code

Improving Deep Learning Interpretability by Saliency Guided Training

1 code implementation NeurIPS 2021 Aya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi

In this paper, we tackle this issue and introduce a {\it saliency guided training}procedure for neural networks to reduce noisy gradients used in predictions while retaining the predictive performance of the model.

Time Series Time Series Analysis

Improving Long-Horizon Forecasts with Expectation-Biased LSTM Networks

no code implementations18 Apr 2018 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 forecasts, e. g given a set of predictor features, forecast a target value for the next few time steps in the future.


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