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Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

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Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

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InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Incorporating Projective Geometry into Deep Learning

On the number of regions of piecewise linear neural networks

Machine Learning for Modeling Stock Returns

Enabling Uncertainty Estimation in Iterative Neural Networks

Intraday solar irradiance forecasting using public cameras