Morteza Ramezani

Orcid: 0000-0002-7498-5522

According to our database1, Morteza Ramezani authored at least 9 papers between 2014 and 2024.

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Bibliography

2024
LiGNN: Graph Neural Networks at LinkedIn.
CoRR, 2024

2022
Predicting Protein-Ligand Docking Structure with Graph Neural Network.
J. Chem. Inf. Model., 2022

Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

GraphGuess: Approximate Graph Processing System with Adaptive Correction.
Proceedings of the Euro-Par 2022: Parallel Processing, 2022

2021
On the Importance of Sampling in Learning Graph Convolutional Networks.
CoRR, 2021

On Provable Benefits of Depth in Training Graph Convolutional Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
GCN meets GPU: Decoupling "When to Sample" from "How to Sample".
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017
Exploring the impact of memory block permutation on performance of a crossbar ReRAM main memory.
Proceedings of the 2017 IEEE International Symposium on Workload Characterization, 2017

2014
CEDAR: Modeling impact of component error derating and read frequency on system-level vulnerability in high-performance processors.
Microelectron. Reliab., 2014


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