Lakshmi Sathidevi

FlowGNN: A Dataflow Architecture for Universal Graph Neural Network Inference via Multi-Queue Streaming

Rishov Sarkar, Stefan Abi-Karam, Yuqiang He, 2022, ArXiv.

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Eva L. Dyer, Erik C. Johnson, Ran Liu, 2023, NeurIPS.

FlowGNN: A Dataflow Architecture for Real-Time Workload-Agnostic Graph Neural Network Inference

Rishov Sarkar, Stefan Abi-Karam, Yuqiang He, 2022, 2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA).

GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration

Cong Hao, Stefan Abi-Karam, Yuqi He, 2022, ArXiv.

Half-Hop: A graph upsampling approach for slowing down message passing

Eva L. Dyer, Petar Velickovic, Shantanu Thakoor, 2023, ICML.

LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration

Eva L. Dyer, Z. Kira, Ran Liu, 2023, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

PreAxC: Error Distribution Prediction for Approximate Computing Quality Control using Graph Neural Networks

Nan Wu, Lakshmi Sathidevi, Xun Jiao, 2023, 2023 24th International Symposium on Quality Electronic Design (ISQED).