Hesham Mostafa

46 papers A* 4A 3C 2Journal 31Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Distributed Training of Large Graph Neural Networks With Variable Communication Rates. IEEE Trans. Signal Inf. Process. over Networks Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
2025	J	`jnl`	Early Attentive Sparsification Accelerates Neural Speech Transcription. CoRR Zifei Xu, Sayeh Sharify, Hesham Mostafa, Tristan Webb, Wanzin Yazar, Xin Wang
2025	A*	`conf`	Fully-inductive Node Classification on Arbitrary Graphs. ICLR Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Jian Tang
2024	J	`jnl`	Distributed Training of Large Graph Neural Networks with Variable Communication Rates. CoRR Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
2024	A	`conf`	FloorSet - a VLSI Floorplanning Dataset with Design Constraints of Real-World SOCs. ICCAD Uday Mallappa, Hesham Mostafa, Mikhail Galkin, Mariano Phielipp, Somdeb Majumdar
2024	J	`jnl`	FloorSet - a VLSI Floorplanning Dataset with Design Constraints of Real-World SoCs. CoRR Uday Mallappa, Hesham Mostafa, Michael Galkin, Mariano Phielipp, Somdeb Majumdar
2024	J	`jnl`	GraphAny: A Foundation Model for Node Classification on Any Graph. CoRR Jianan Zhao, Hesham Mostafa, Mikhail Galkin, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang
2024	—	`conf`	MinBLoG: Minimization of Boolean Logic Functions using Graph Attention Network. MLCAD Prianka Sengupta, Aakash Tyagi, Jiang Hu, Vivek K. Rajan, Hesham Mostafa, Somdeb Majumdar
2024	J	`jnl`	PARSAC: Fast, Human-quality Floorplanning for Modern SoCs with Complex Design Constraints. CoRR Hesham Mostafa, Uday Mallappa, Mikhail Galkin, Mariano Phielipp, Somdeb Majumdar
2024	A*	`conf`	Towards Foundation Models for Knowledge Graph Reasoning. ICLR Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
2023	A	`conf`	Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. WACV Shengyu Feng, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar, Subarna Tripathi
2023	J	`jnl`	FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR Hesham Mostafa, Adam Grabowski, Md Asadullah Turja, Juan Cerviño, Alejandro Ribeiro, Nageen Himayat
2023	A	`conf`	Generative Graph Augmentation for Minority Class in Fraud Detection. CIKM Lin Meng, Hesham Mostafa, Marcel Nassar, Xiaonan Zhang, Jiawei Zhang
2023	J	`jnl`	Towards Foundation Models for Knowledge Graph Reasoning. CoRR Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
2022	—	`conf`	Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. MLSys Hesham Mostafa
2021	J	`jnl`	Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs. CoRR Shengyu Feng, Subarna Tripathi, Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
2021	A*	`conf`	Implicit SVD for Graph Representation Learning. NeurIPS Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	Implicit SVD for Graph Representation Learning. CoRR Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan
2021	J	`jnl`	On Local Aggregation in Heterophilic Graphs. CoRR Hesham Mostafa, Marcel Nassar, Somdeb Majumdar
2021	J	`jnl`	Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs. CoRR Hesham Mostafa
2020	J	`jnl`	Attention-based Image Upsampling. CoRR Souvik Kundu, Hesham Mostafa, Sharath Nittur Sridhar, Sairam Sundaresan
2020	J	`jnl`	Permutohedral-GCN: Graph Convolutional Networks with Global Attention. CoRR Hesham Mostafa, Marcel Nassar
2019	J	`jnl`	NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps. IEEE Trans. Neural Networks Learn. Syst. 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 Delbruck
2019	J	`jnl`	Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization. CoRR Hesham Mostafa, Xin Wang
2019	A*	`conf`	Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization. ICML Hesham Mostafa, Xin Wang
2019	J	`jnl`	Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters. CoRR Hesham Mostafa
2019	—	`conf`	Single-Bit-per-Weight Deep Convolutional Neural Networks without Batch-Normalization Layers for Embedded Systems. ACIRS Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
2019	J	`jnl`	Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems. CoRR Mark D. McDonnell, Hesham Mostafa, Runchun Wang, André van Schaik
2019	J	`jnl`	Surrogate Gradient Learning in Spiking Neural Networks. CoRR Emre O. Neftci, Hesham Mostafa, Friedemann Zenke
2019	J	`jnl`	Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks. IEEE Signal Process. Mag. Emre O. Neftci, Hesham Mostafa, Friedemann Zenke
2018	J	`jnl`	A Learning Framework for Winner-Take-All Networks with Stochastic Synapses. Neural Comput. Hesham Mostafa, Gert Cauwenberghs
2018	—	`conf`	Small-footprint Spiking Neural Networks for Power-efficient Keyword Spotting. BioCAS Bruno U. Pedroni, Sadique Sheik, Hesham Mostafa, Somnath Paul, Charles Augustine, Gert Cauwenberghs
2018	J	`jnl`	Supervised Learning Based on Temporal Coding in Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Hesham Mostafa
2018	J	`jnl`	Synaptic Plasticity Dynamics for Deep Continuous Local Learning. CoRR Jacques Kaiser, Hesham Mostafa, Emre Neftci
2017	J	`jnl`	A learning framework for winner-take-all networks with stochastic synapses. CoRR Hesham Mostafa, Gert Cauwenberghs
2017	J	`jnl`	Deep supervised learning using local errors. CoRR Hesham Mostafa, Vishwajith Ramesh, Gert Cauwenberghs
2017	J	`jnl`	NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps. CoRR 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 Delbruck
2016	C	`conf`	Beyond spike-timing dependent plasticity in memristor crossbar arrays. ISCAS Hesham Mostafa, Christian Mayr, Giacomo Indiveri
2016	J	`jnl`	Supervised learning based on temporal coding in spiking neural networks. CoRR Hesham Mostafa
2015	J	`jnl`	An event-based architecture for solving constraint satisfaction problems. CoRR Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
2015	J	`jnl`	Rhythmic Inhibition Allows Neural Networks to Search for Maximally Consistent States. Neural Comput. Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
2015	J	`jnl`	Stochastic Interpretation of Quasi-periodic Event-based Systems. CoRR Hesham Mostafa, Giacomo Indiveri
2014	C	`conf`	A hybrid analog/digital Spike-Timing Dependent Plasticity learning circuit for neuromorphic VLSI multi-neuron architectures. ISCAS Hesham Mostafa, Federico Corradi, Fabio Stefanini, Giacomo Indiveri
2014	J	`jnl`	Sequential Activity in Asymmetrically Coupled Winner-Take-All Circuits. Neural Comput. Hesham Mostafa, Giacomo Indiveri
2013	—	`conf`	Automated synthesis of asynchronous event-based interfaces for neuromorphic systems. ECCTD Hesham Mostafa, Federico Corradi, Marc Osswald, Giacomo Indiveri
2013	—	`conf`	Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems. NIPS Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri