Structured video representation in the form of dynamic scene graphs is a...
We present the Sequential Aggregation and Rematerialization (SAR) scheme...
Many recent works have studied the performance of Graph Neural Networks
...
Convolutional layers are an integral part of many deep neural network
so...
Graph convolutional networks (GCNs) update a node's feature vector by
ag...
Federated learning is a distributed, privacy-aware learning scenario whi...
Batch-normalization (BN) layers are thought to be an integrally importan...
Deep neural networks are typically highly over-parameterized with prunin...
A growing number of neuromorphic spiking neural network processors that
...
A growing body of work underlines striking similarities between spiking
...
Error backpropagation is a highly effective mechanism for learning
high-...
Many recent generative models make use of neural networks to transform t...
Artificial neural networks (ANNs) trained using backpropagation are powe...
Convolutional neural networks (CNNs) have become the dominant neural net...
Gradient descent training techniques are remarkably successful in traini...
Many networks used in machine learning and as models of biological neura...