| Spike-thrift: Towards energy-efficient deep spiking neural networks by limiting spiking activity via attention-guided compression S Kundu, G Datta, M Pedram, PA Beerel Proceedings of the IEEE/CVF winter conference on applications of computer …, 2021 | 129 | 2021 |
| HIRE-SNN: Harnessing the inherent robustness of energy-efficient deep spiking neural networks by training with crafted input noise S Kundu, M Pedram, PA Beerel Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 91 | 2021 |
| DNR: A tunable robust pruning framework through dynamic network rewiring of dnns S Kundu, M Nazemi, PA Beerel, M Pedram Proceedings of the 26th Asia and South Pacific Design Automation Conference …, 2021 | 76 | 2021 |
| A novel approach to predict COVID-19 using support vector machine S Guhathakurata, S Kundu, A Chakraborty, JS Banerjee Data Science for COVID-19, 351-364, 2021 | 71 | 2021 |
| Exploiting explicit paths for multi-hop reading comprehension S Kundu, T Khot, A Sabharwal, P Clark arXiv preprint arXiv:1811.01127, 2018 | 65 | 2018 |
| Pre-defined sparsity for low-complexity convolutional neural networks S Kundu, M Nazemi, M Pedram, KM Chugg, PA Beerel IEEE Transactions on Computers 69 (7), 1045-1058, 2020 | 53 | 2020 |
| GEAR: An efficient KV cache compression recipe for near-lossless generative inference of LLM H Kang, Q Zhang, S Kundu, G Jeong, Z Liu, T Krishna, T Zhao 🏆 NeurIPS Workshop 2024 (best paper honorable mention), 2024 | 52 | 2024 |
| Pipeedge: Pipeline parallelism for large-scale model inference on heterogeneous edge devices Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JP Walters 2022 25th Euromicro Conference on Digital System Design (DSD), 298-307, 2022 | 49* | 2022 |
| A processing-in-pixel-in-memory paradigm for resource-constrained tinyml applications S Kundu*, G Datta*, Z Yin, RT Lakkireddy, J Mathai, AP Jacob, PA Beerel, ... Scientific Reports 12 (1), 14396, 2022 | 44 | 2022 |
| Training energy-efficient deep spiking neural networks with single-spike hybrid input encoding G Datta, S Kundu, PA Beerel 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 43 | 2021 |
| Learning to linearize deep neural networks for secure and efficient private inference S Kundu, S Lu, Y Zhang, J Liu, PA Beerel International Conference on Learning Representation (ICLR) 2023, 2023 | 39 | 2023 |
| Analyzing the confidentiality of undistillable teachers in knowledge distillation S Kundu, Q Sun, Y Fu, M Pedram, P Beerel Advances in Neural Information Processing Systems (NeurIPS) 2021 34, 9181-9192, 2021 | 33 | 2021 |
| ACE-SNN: Algorithm-hardware co-design of energy-efficient & low-latency deep spiking neural networks for 3d image recognition G Datta, S Kundu, AR Jaiswal, PA Beerel Frontiers in neuroscience 16, 815258, 2022 | 32 | 2022 |
| Fusing models with complementary expertise H Wang, FM Polo, Y Sun, S Kundu, E Xing, M Yurochkin International Conference on Learning Representation (ICLR) 2024, 2023 | 30 | 2023 |
| Vision-HGNN: An Image is More Than a Graph of Nodes Y Han, P Wang, S Kundu, Y Ding, Z Wang IEEE/CVF International Conference on Computer Vision (ICCV) 2023, 19878-19888, 2023 | 29 | 2023 |
| Memristors enabled computing correlation parameter in-memory system: A potential alternative to von Neumann architecture S Kundu, PB Ganganaik, J Louis, H Chalamalasetty, BP Rao IEEE Transactions on Very Large Scale Integration (VLSI) Systems 30 (6), 755-768, 2022 | 29 | 2022 |
| Attentionlite: Towards efficient self-attention models for vision S Kundu, S Sundaresan ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 27 | 2021 |
| Revisiting Sparsity Hunting in Federated Learning: Why does Sparsity Consensus Matter? S Kundu*, S Babakniya*, S Prakash, Y Niu, S Avestimehr Transactions on Machine Learning Research (TMLR) 2023, 2023 | 25* | 2023 |
| ViTA: A vision transformer inference accelerator for edge applications S Nag, G Datta, S Kundu, N Chandrachoodan, PA Beerel 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2023 | 24 | 2023 |
| Towards low-latency energy-efficient deep snns via attention-guided compression S Kundu, G Datta, M Pedram, PA Beerel arXiv preprint arXiv:2107.12445, 2021 | 22 | 2021 |
Peter BeerelProfessor of Electrical and Computer Engineering, USC確認したメール アドレス: usc.edu