Exploring Lottery Ticket Hypothesis in Spiking Neural Networks Y Kim, Y Li, H Park, Y Venkatesha, R Yin, P Panda European Conference on Computer Vision (ECCV) 2022, 102-120, 2022 | 61 | 2022 |
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks R Yin, A Moitra, A Bhattacharjee, Y Kim, P Panda IEEE Transactions on Computer-aided Design of Integrated Circuits and …, 2022 | 60 | 2022 |
uGEMM: Unary Computing Architecture for GEMM Applications D Wu, J Li, R Yin, H Hsiao, Y Kim, J San Miguel International Symposium on Computer Architecture (ISCA) 2020, 377-390, 2020 | 55 | 2020 |
MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks R Yin, Y Li, A Moitra, P Panda Asia and South Pacific Design Automation Conference (ASP-DAC) 2024, 830-835, 2024 | 22 | 2024 |
Efficient Human Activity Recognition with Spatio-temporal Spiking Neural Networks Y Li, R Yin, Y Kim, P Panda Frontiers in Neuroscience 17, 1233037, 2023 | 22 | 2023 |
Workload-balanced Pruning for Sparse Spiking Neural Networks R Yin, Y Kim, Y Li, A Moitra, N Satpute, A Hambitzer, P Panda IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) 8 …, 2024 | 18 | 2024 |
uGEMM: Unary Computing for GEMM Applications D Wu, J Li, R Yin, H Hsiao, Y Kim, J San Miguel IEEE Micro 41 (3), 50-56, 2021 | 16* | 2021 |
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks Y Kim, Y Li, A Moitra, R Yin, P Panda Frontiers in Neuroscience 17, 1230002, 2023 | 11 | 2023 |
Normalized Stability: A Cross-level Design Metric for Early Termination in Stochastic Computing D Wu, R Yin, JS Miguel Asia and South Pacific Design Automation Conference (ASP-DAC) 2021, 254-259, 2021 | 11 | 2021 |
Are SNNs Truly Energy-efficient?—A Hardware Perspective A Bhattacharjee*, R Yin*, A Moitra*, P Panda IEEE International Conference on Acoustics, Speech and Signal Processing …, 2024 | 10 | 2024 |
In-stream Correlation-based Division and Bit-inserting Square Root in Stochastic Computing D Wu, R Yin, J San Miguel IEEE Design & Test 38 (6), 53-59, 2021 | 9 | 2021 |
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training D Lee, R Yin, Y Kim, A Moitra, Y Li, P Panda Design, Automation and Test in Europe Conference (DATE) 2024, 2024 | 5 | 2024 |
Rethinking Skip Connections in Spiking Neural Networks with Time-To-First-Spike Coding Y Kim, A Kahana, R Yin, Y Li, P Stinis, GE Karniadakis, P Panda Frontiers in Neuroscience 18, 1346805, 2024 | 4 | 2024 |
Do we really need a large number of visual prompts? Y Kim, Y Li, A Moitra, R Yin, P Panda Neural Networks 177, 106390, 2024 | 3 | 2024 |
LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks R Yin, Y Kim, D Wu, P Panda International Symposium on Microarchitecture (MICRO) 2024, 1107-1121, 2024 | 2 | 2024 |
PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs R Yin, Y Li, P Panda 62nd Design Automation Conference (DAC) 2025, 2025 | | 2025 |
Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing A Moitra, R Yin, P Panda Great Lakes Symposium on VLSI (GLSVSI) 2023, 137-138, 2023 | | 2023 |