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Theory of Deep Learning: Neural Tangent Kernel and Beyond

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Theory of Deep Learning: Neural Tangent Kernel and Beyond

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

Biologically plausible deep learning – but how far can we go with shallow networks?

Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Incremental Learning Meets Reduced Precision Networks

Language Independent Query by Example Spoken Term Detection

A jamming transition from under- to over-parametrization affects generalization in deep learning

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Training fully connected networks with resistive memories: impact of device failures

LAF-Net: Locally Adaptive Fusion Networks for Stereo Confidence Estimation

Incremental Learning Meets Reduced Precision Networks

Language Independent Query by Example Spoken Term Detection

Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Biologically plausible deep learning – but how far can we go with shallow networks?

LAF-Net: Locally Adaptive Fusion Networks for Stereo Confidence Estimation

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

A jamming transition from under- to over-parametrization affects generalization in deep learning

Training fully connected networks with resistive memories: impact of device failures

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Analog Neural Networks with Deep-submicron Nonlinear Synapses