| A compute-in-memory chip based on resistive random-access memory W Wan, R Kubendran, C Schaefer, SB Eryilmaz, W Zhang, D Wu, S Deiss, ... Nature 608 (7923), 504-512, 2022 | 318 | 2022 |
| Supervised learning in all FeFET-based spiking neural network: Opportunities and challenges S Dutta, C Schafer, J Gomez, K Ni, S Joshi, S Datta Frontiers in neuroscience 14, 634, 2020 | 76 | 2020 |
| Quantizing spiking neural networks with integers CJS Schaefer, S Joshi International Conference on Neuromorphic Systems 2020, 1-8, 2020 | 21 | 2020 |
| Neurobench: Advancing neuromorphic computing through collaborative, fair and representative benchmarking J Yik, SH Ahmed, Z Ahmed, B Anderson, AG Andreou, C Bartolozzi, ... arXiv preprint arXiv:2304.04640, 2023 | 11 | 2023 |
| LSTMS for keyword spotting with reram-based compute-in-memory architectures CJS Schaefer, M Horeni, P Taheri, S Joshi 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021 | 7 | 2021 |
| Edge Inference with Fully Differentiable Quantized Mixed Precision Neural Networks CJS Schaefer, S Joshi, S Li, R Blazquez Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024 | 6 | 2024 |
| The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks CJS Schaefer, P Taheri, M Horeni, S Joshi IEEE Transactions on Circuits and Systems II: Express Briefs, 2023 | 5 | 2023 |
| Analog vs. digital spatial transforms: A throughput, power, and area comparison ZM Enciso, SH Mirfarshbafan, O Castañeda, CJS Schaefer, C Studer, ... 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems …, 2020 | 5 | 2020 |
| Estimating Post-Synaptic Effects for Online Training of Feed-Forward SNNs T Summe, CJS Schaefer, S Joshi arXiv preprint arXiv:2311.16151, 2023 | 1 | 2023 |
| Mixed Precision Post Training Quantization of Neural Networks with Sensitivity Guided Search CJS Schaefer, E Guo, C Stanton, X Zhang, T Jablin, N Lambert-Shirzad, ... arXiv preprint arXiv:2302.01382, 2023 | 1 | 2023 |
| Memory Organization for Energy-Efficient Learning and Inference in Digital Neuromorphic Accelerators CJS Schaefer, P Faley, EO Neftci, S Joshi 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020 | 1 | 2020 |
| Hadamard Domain Training with Integers for Class Incremental Quantized Learning M Schiemer, CJS Schaefer, JP Vap, MJ Horeni, YE Wang, J Ye, S Joshi arXiv preprint arXiv:2310.03675, 2023 | | 2023 |
| Augmenting Hessians with Inter-Layer Dependencies for Mixed-Precision Post-Training Quantization CJS Schaefer, N Lambert-Shirzad, X Zhang, C Chou, T Jablin, J Li, E Guo, ... arXiv preprint arXiv:2306.04879, 2023 | | 2023 |
| Hardware-aware Quantization for Biologically Inspired Machine Learning and Inference CJS Schaefer University of Notre Dame, 2023 | | 2023 |
| Memory Organization and Structures for On-Chip Learning in Spiking Neural Networks CJS Schaefer, S Joshi 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems …, 2020 | | 2020 |
| Memory Organization for Energy-Efficient Learning and Inference in Digital Neuromorphic CJS Schaefer, P Faley, EO Neftci | | 2020 |
Siddharth JoshiAssistant Professor at University of Notre Dame, Dept. of Comp. Science and Eng. and Dept. ofVerified email at nd.edu
