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A Critical Re-evaluation of Neural Methods for Entity Alignment

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A Critical Re-evaluation of Neural Methods for Entity Alignment

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On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Capsule networks as recurrent models of grouping and segmentation

Crowding reveals fundamental differences in local vs. global processing in humans and machines

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

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

Learning Vision-based Flight in Drone Swarms by Imitation

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Analog Neural Networks with Deep-submicron Nonlinear Synapses

An improved objective metric to predict image quality using deep neural networks

Deep Semantic Segmentation Using Nir As Extra Physical Information

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Capsule networks as recurrent models of grouping and segmentation

Crowding reveals fundamental differences in local vs. global processing in humans and machines

An improved objective metric to predict image quality using deep neural networks

Deep Semantic Segmentation Using Nir As Extra Physical Information

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

Learning Vision-based Flight in Drone Swarms by Imitation

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

Analog Neural Networks with Deep-submicron Nonlinear Synapses

Analog Neural Networks with Deep-submicron Nonlinear Synapses