| FlowGNN: A dataflow architecture for real-time workload-agnostic graph neural network inference R Sarkar, S Abi-Karam, Y He, L Sathidevi, C Hao 2023 IEEE International Symposium on High-Performance Computer Architecture …, 2023 | 18 | 2023 |
| Flowgnn: A dataflow architecture for universal graph neural network inference via multi-queue streaming R Sarkar, S Abi-Karam, Y He, L Sathidevi, C Hao arXiv preprint arXiv:2204.13103, 2022 | 11 | 2022 |
| Gengnn: A generic fpga framework for graph neural network acceleration S Abi-Karam, Y He, R Sarkar, L Sathidevi, Z Qiao, C Hao arXiv preprint arXiv:2201.08475, 2022 | 11 | 2022 |
| Half-Hop: A graph upsampling approach for slowing down message passing M Azabou, V Ganesh, S Thakoor, CH Lin, L Sathidevi, R Liu, M Valko, ... International Conference on Machine Learning, 1341-1360, 2023 | 6 | 2023 |
| Mtneuro: A benchmark for evaluating representations of brain structure across multiple levels of abstraction J Quesada, L Sathidevi, R Liu, N Ahad, J Jackson, M Azabou, J Xiao, ... Advances in neural information processing systems 35, 5299-5314, 2022 | 3 | 2022 |
| Optimization of hybrid CMOS designs using a new energy efficient 1 bit hybrid full adder S Lakshmi, CM Raj, D Krishnadas 2018 3rd International Conference on Communication and Electronics Systems …, 2018 | 3 | 2018 |
| PreAxC: Error Distribution Prediction for Approximate Computing Quality Control using Graph Neural Networks L Sathidevi, A Sharma, N Wu, X Jiao, C Hao 2023 24th International Symposium on Quality Electronic Design (ISQED), 1-7, 2023 | 1 | 2023 |
| LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration R Liu, S Khose, J Xiao, L Sathidevi, K Ramnath, Z Kira, EL Dyer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | | 2024 |
