Hesham Mostafa

Orcid: 0000-0003-1737-0182

According to our database1, Hesham Mostafa authored at least 28 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2023
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs.
CoRR, 2023

Towards Foundation Models for Knowledge Graph Reasoning.
CoRR, 2023

Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Generative Graph Augmentation for Minority Class in Fraud Detection.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs.
Proceedings of Machine Learning and Systems 2022, 2022

2021
On Local Aggregation in Heterophilic Graphs.
CoRR, 2021

Implicit SVD for Graph Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Attention-based Image Upsampling.
CoRR, 2020

Permutohedral-GCN: Graph Convolutional Networks with Global Attention.
CoRR, 2020

2019
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps.
IEEE Trans. Neural Networks Learn. Syst., 2019

Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks.
IEEE Signal Process. Mag., 2019

Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters.
CoRR, 2019

Surrogate Gradient Learning in Spiking Neural Networks.
CoRR, 2019

Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems.
Proceedings of the 4th Asia-Pacific Conference on Intelligent Robot Systems, 2019

2018
Supervised Learning Based on Temporal Coding in Spiking Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., 2018

A Learning Framework for Winner-Take-All Networks with Stochastic Synapses.
Neural Comput., 2018

Synaptic Plasticity Dynamics for Deep Continuous Local Learning.
CoRR, 2018

Small-footprint Spiking Neural Networks for Power-efficient Keyword Spotting.
Proceedings of the 2018 IEEE Biomedical Circuits and Systems Conference, 2018

2017
Deep supervised learning using local errors.
CoRR, 2017

2016
Beyond spike-timing dependent plasticity in memristor crossbar arrays.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

2015
Rhythmic Inhibition Allows Neural Networks to Search for Maximally Consistent States.
Neural Comput., 2015

An event-based architecture for solving constraint satisfaction problems.
CoRR, 2015

Stochastic Interpretation of Quasi-periodic Event-based Systems.
CoRR, 2015

2014
Sequential Activity in Asymmetrically Coupled Winner-Take-All Circuits.
Neural Comput., 2014

A hybrid analog/digital Spike-Timing Dependent Plasticity learning circuit for neuromorphic VLSI multi-neuron architectures.
Proceedings of the IEEE International Symposium on Circuits and Systemss, 2014

2013
Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Automated synthesis of asynchronous event-based interfaces for neuromorphic systems.
Proceedings of the 21st European Conference on Circuit Theory and Design, 2013


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