Hesham Mostafa

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 34

Top Topics

Graph Representation

Keyword Spotting

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
GraphAny: A Foundation Model for Node Classification on Any Graph. CoRR (2024)
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
Towards Foundation Models for Knowledge Graph Reasoning. ICLR (2024)
Uday Mallappa, Hesham Mostafa, Michael Galkin, Mariano Phielipp, Somdeb Majumdar
FloorSet - a VLSI Floorplanning Dataset with Design Constraints of Real-World SoCs. CoRR (2024)
Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
Distributed Training of Large Graph Neural Networks with Variable Communication Rates. CoRR (2024)
Hesham Mostafa, Uday Mallappa, Mikhail Galkin, Mariano Phielipp, Somdeb Majumdar
PARSAC: Fast, Human-quality Floorplanning for Modern SoCs with Complex Design Constraints. CoRR (2024)
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
Towards Foundation Models for Knowledge Graph Reasoning. CoRR (2023)
Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang
Generative Graph Augmentation for Minority Class in Fraud Detection. CIKM (2023)
Hesham Mostafa, Adam Grabowski, Md Asadullah Turja, Juan Cerviño, Alejandro Ribeiro, Nageen Himayat
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR (2023)
Shengyu Feng, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar, Subarna Tripathi
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. WACV (2023)
Hesham Mostafa
Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. MLSys (2022)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. NeurIPS (2021)
Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
Implicit SVD for Graph Representation Learning. CoRR (2021)
Hesham Mostafa
Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. CoRR (2021)
Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
On Local Aggregation in Heterophilic Graphs. CoRR (2021)
Shengyu Feng, Subarna Tripathi, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. CoRR (2021)
Hesham Mostafa, Marcel Nassar
Permutohedral-GCN: Graph Convolutional Networks with Global Attention. CoRR (2020)
Souvik Kundu, Hesham Mostafa, Sharath Nittur Sridhar, Sairam Sundaresan
Attention-based Image Upsampling. CoRR (2020)
Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems. ACIRS (2019)
Emre O. Neftci, Hesham Mostafa, Friedemann Zenke
Surrogate Gradient Learning in Spiking Neural Networks. CoRR (2019)
Emre O. Neftci, Hesham Mostafa, Friedemann Zenke
Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks. IEEE Signal Process. Mag. 36 (6) (2019)
Hesham Mostafa, Xin Wang
Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization. ICML (2019)
Alessandro Aimar, Hesham Mostafa, Enrico Calabrese, Antonio Rios-Navarro, Ricardo Tapiador-Morales, Iulia-Alexandra Lungu, Moritz B. Milde, Federico Corradi, Alejandro Linares-Barranco, Shih-Chii Liu, Tobi Delbrück
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps. IEEE Trans. Neural Networks Learn. Syst. 30 (3) (2019)
Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems. CoRR (2019)
Hesham Mostafa
Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters. CoRR (2019)
Hesham Mostafa, Xin Wang
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization. CoRR (2019)
Bruno U. Pedroni, Sadique Sheik, Hesham Mostafa, Somnath Paul, Charles Augustine, Gert Cauwenberghs
Small-footprint Spiking Neural Networks for Power-efficient Keyword Spotting. BioCAS (2018)
Jacques Kaiser, Hesham Mostafa, Emre Neftci
Synaptic Plasticity Dynamics for Deep Continuous Local Learning. CoRR (2018)
Hesham Mostafa
Supervised Learning Based on Temporal Coding in Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 29 (7) (2018)
Hesham Mostafa, Gert Cauwenberghs
A Learning Framework for Winner-Take-All Networks with Stochastic Synapses. Neural Comput. 30 (6) (2018)
Hesham Mostafa, Vishwajith Ramesh, Gert Cauwenberghs
Deep supervised learning using local errors. CoRR (2017)
Alessandro Aimar, Hesham Mostafa, Enrico Calabrese, Antonio Rios-Navarro, Ricardo Tapiador-Morales, Iulia-Alexandra Lungu, Moritz B. Milde, Federico Corradi, Alejandro Linares-Barranco, Shih-Chii Liu, Tobi Delbrück
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps. CoRR (2017)
Hesham Mostafa, Gert Cauwenberghs
A learning framework for winner-take-all networks with stochastic synapses. CoRR (2017)
Hesham Mostafa
Supervised learning based on temporal coding in spiking neural networks. CoRR (2016)
Hesham Mostafa, Christian Mayr, Giacomo Indiveri
Beyond spike-timing dependent plasticity in memristor crossbar arrays. ISCAS (2016)
Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
An event-based architecture for solving constraint satisfaction problems. CoRR (2015)
Hesham Mostafa, Giacomo Indiveri
Stochastic Interpretation of Quasi-periodic Event-based Systems. CoRR (2015)
Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
Rhythmic Inhibition Allows Neural Networks to Search for Maximally Consistent States. Neural Comput. 27 (12) (2015)
Hesham Mostafa, Federico Corradi, Fabio Stefanini, Giacomo Indiveri
A hybrid analog/digital Spike-Timing Dependent Plasticity learning circuit for neuromorphic VLSI multi-neuron architectures. ISCAS (2014)
Hesham Mostafa, Giacomo Indiveri
Sequential Activity in Asymmetrically Coupled Winner-Take-All Circuits. Neural Comput. 26 (9) (2014)
Hesham Mostafa, Federico Corradi, Marc Osswald, Giacomo Indiveri
Automated synthesis of asynchronous event-based interfaces for neuromorphic systems. ECCTD (2013)
Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems. NIPS (2013)