| Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures C Lee, SS Sarwar, P Panda, G Srinivasan, K Roy Frontiers in Neuroscience 14, 2020 | 526* | 2020 |
| X-sram: Enabling in-memory boolean computations in cmos static random access memories A Agrawal, A Jaiswal, C Lee, K Roy IEEE Transactions on Circuits and Systems I: Regular Papers, 1-14, 2018 | 328 | 2018 |
| Training deep spiking convolutional neural networks with STDP-based unsupervised pre-training followed by supervised fine-tuning C Lee, P Panda, G Srinivasan, K Roy Frontiers in neuroscience 12, 435, 2018 | 247 | 2018 |
| Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks C Lee, A Kosta, AZ Zhu, K Chaney, K Daniilidis, K Roy In proceedings of European Conference on Computer Vision (ECCV), 2020, 2020 | 207 | 2020 |
| Deep spiking convolutional neural network trained with unsupervised spike-timing-dependent plasticity C Lee, G Srinivasan, P Panda, K Roy IEEE Transactions on Cognitive and Developmental Systems 11 (3), 384-394, 2018 | 172 | 2018 |
| A comprehensive analysis on adversarial robustness of spiking neural networks S Sharmin, P Panda, SS Sarwar, C Lee, W Ponghiran, K Roy 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 88 | 2019 |
| NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models C Lee, R Roy, M Xu, J Raiman, M Shoeybi, B Catanzaro, W Ping International Conference on Learning Representations, ICLR 2025 (To appear), 2024 | 68 | 2024 |
| Towards understanding the effect of leak in spiking neural networks C Lee, SS Chowdhury, K Roy Neurocomputing 464, 83-94, 2021 | 63 | 2021 |
| Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures C Lee, AK Kosta, K Roy 2022 IEEE International Conference on Robotics and Automation (ICRA), 2022 | 48 | 2022 |
| Chatqa: Surpassing gpt-4 on conversational qa and rag Z Liu, W Ping, R Roy, P Xu, C Lee, M Shoeybi, B Catanzaro The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 47* | 2024 |
| Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing G Srinivasan, C Lee, A Sengupta, P Panda, SS Sarwar, K Roy ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 30 | 2020 |
| X-CHANGR: Changing Memristive Crossbar Mapping for Mitigating Line-Resistance Induced Accuracy Degradation in Deep Neural Networks A Agrawal, C Lee, K Roy arXiv preprint arXiv:1907.00285, 2019 | 30 | 2019 |
| Self-Supervised Optical Flow with Spiking Neural Networks and Event Based Cameras K Chaney, A Panagopoulou, C Lee, K Roy, K Daniilidis 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 16 | 2021 |
| Noise resilient leaky integrate-and-fire neurons based on multi-domain spintronic devices C Wang, C Lee, K Roy Scientific Reports 12 (1), 8361, 2022 | 14 | 2022 |
| Exploring Spike-Based Learning for Neuromorphic Computing: Prospects and Perspectives N Rathi, A Agrawal, C Lee, AK Kosta, K Roy 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 902-907, 2021 | 14 | 2021 |
| MM-Embed: Universal Multimodal Retrieval with Multimodal LLMs SC Lin, C Lee, M Shoeybi, J Lin, B Catanzaro, W Ping International Conference on Learning Representations, ICLR 2025 (To appear), 2024 | 2 | 2024 |
Kaushik RoyProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu