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Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

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Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

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Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

Predicting optical transmission through complex scattering media from reflection patterns with deep neural networks

ON THE RELATIONSHIP BETWEEN SPEECH-BASED BREATHING SIGNAL PREDICTION EVALUATION MEASURES AND BREATHING PARAMETERS ESTIMATION

On The Relationship Between Speech-Based Breathing Signal Prediction Evaluation Measures And Breathing Parameters Estimation

Biologically plausible unsupervised learning in shallow and deep neural networks

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Supplementary Material - AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

Controlling oscillations in spectral schemes using Artificial Neural Networks

Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

The Unstoppable Rise of Computational Linguistics in Deep Learning

Predicting optical transmission through complex scattering media from reflection patterns with deep neural networks

ON THE RELATIONSHIP BETWEEN SPEECH-BASED BREATHING SIGNAL PREDICTION EVALUATION MEASURES AND BREATHING PARAMETERS ESTIMATION

Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

On The Relationship Between Speech-Based Breathing Signal Prediction Evaluation Measures And Breathing Parameters Estimation

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Biologically plausible unsupervised learning in shallow and deep neural networks

Supplementary Material - AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks

The Unstoppable Rise of Computational Linguistics in Deep Learning

Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

Controlling oscillations in spectral schemes using Artificial Neural Networks