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12/18/2021
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
Structured video representation in the form of dynamic scene graphs is a...
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11/11/2021
Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs
We present the Sequential Aggregation and Rematerialization (SAR) scheme...
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06/06/2021
On Local Aggregation in Heterophilic Graphs
Many recent works have studied the performance of Graph Neural Networks ...
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12/17/2020
Attention-based Image Upsampling
Convolutional layers are an integral part of many deep neural network so...
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03/02/2020
Permutohedral-GCN: Graph Convolutional Networks with Global Attention
Graph convolutional networks (GCNs) update a node's feature vector by ag...
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12/30/2019
Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters
Federated learning is a distributed, privacy-aware learning scenario whi...
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07/16/2019
Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems
Batch-normalization (BN) layers are thought to be an integrally importan...
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02/15/2019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
Deep neural networks are typically highly over-parameterized with prunin...
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01/28/2019
Surrogate Gradient Learning in Spiking Neural Networks
A growing number of neuromorphic spiking neural network processors that ...
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11/27/2018
Synaptic Plasticity Dynamics for Deep Continuous Local Learning
A growing body of work underlines striking similarities between spiking ...
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11/17/2017
Deep supervised learning using local errors
Error backpropagation is a highly effective mechanism for learning high-...
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08/14/2017
A learning framework for winner-take-all networks with stochastic synapses
Many recent generative models make use of neural networks to transform t...
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06/15/2017
Hardware-efficient on-line learning through pipelined truncated-error backpropagation in binary-state networks
Artificial neural networks (ANNs) trained using backpropagation are powe...
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06/05/2017
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Convolutional neural networks (CNNs) have become the dominant neural net...
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06/27/2016
Supervised learning based on temporal coding in spiking neural networks
Gradient descent training techniques are remarkably successful in traini...
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12/09/2015
