| Event-driven contrastive divergence for spiking neuromorphic systems E Neftci, S Das, B Pedroni, K Kreutz-Delgado, G Cauwenberghs Frontiers in neuroscience 7, 69689, 2014 | 256 | 2014 |
| A design methodology for efficient implementation of deconvolutional neural networks on an FPGA X Zhang University of California, San Diego, 2017 | 48 | 2017 |
| Method and apparatus for controlling the programming and erasing of flash memory P Wang, S Das US Patent 6,421,757, 2002 | 40 | 2002 |
| Predictive inference for locally stationary time series with an application to climate data S Das, DN Politis Journal of the American Statistical Association 116 (534), 919-934, 2021 | 31 | 2021 |
| Mapping generative models onto a network of digital spiking neurons BU Pedroni, S Das, JV Arthur, PA Merolla, BL Jackson, DS Modha, ... IEEE transactions on biomedical circuits and systems 10 (4), 837-854, 2016 | 27 | 2016 |
| System and method for facilitating data transfer using a shared non-deterministic bus S Das, P Crary, A Raykhman US Patent 8,848,731, 2014 | 24 | 2014 |
| Gibbs sampling with low-power spiking digital neurons S Das, BU Pedroni, P Merolla, J Arthur, AS Cassidy, BL Jackson, ... 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2704-2707, 2015 | 22 | 2015 |
| A competitive edge: Can FPGAs beat GPUs at DCNN inference acceleration in resource-limited edge computing applications? I Colbert, J Daly, K Kreutz-Delgado, S Das arXiv preprint arXiv:2102.00294, 2021 | 19 | 2021 |
| Nonparametric estimation of the conditional distribution at regression boundary points S Das, DN Politis The American Statistician, 2019 | 15 | 2019 |
| AX-DBN: An approximate computing framework for the design of low-power discriminative deep belief networks I Colbert, K Kreutz-Delgado, S Das 2019 International Joint Conference on Neural Networks (IJCNN), 1-9, 2019 | 12* | 2019 |
| Neuromorphic adaptations of restricted boltzmann machines and deep belief networks BU Pedroni, S Das, E Neftci, K Kreutz-Delgado, G Cauwenberghs The 2013 international joint conference on neural networks (IJCNN), 1-6, 2013 | 12 | 2013 |
| Training deep neural networks with joint quantization and pruning of weights and activations X Zhang, I Colbert, K Kreutz-Delgado, S Das arXiv preprint arXiv:2110.08271, 2021 | 9 | 2021 |
| Clock divider system and method with incremental adjustment steps while controlling tolerance in clock duty cycle S Das, H Zhu, KR Bowles, ML Severson US Patent 8,433,944, 2013 | 9 | 2013 |
| Restricted boltzmann machines and continuous-time contrastive divergence in spiking neuromorphic systems E Neftci, S Das, B Pedroni, K Kreutz-Delgado, G Cauwenberghs May, 2013 | 8 | 2013 |
| Deterministic networking (DetNet) security considerations T Mizrahi, E Grossman, AJ Hacker, S Das, J Dowdell, H Austad, K Stanton, ... Internet Engineering Task Force, Internet-Draft draftietf-detnet-security-01, 2017 | 7 | 2017 |
| System and Method for Facilitating Data Transfer Between a First Clock Domain and a Second Clock Domain S Das, P Crary, A Raykhman US Patent App. 13/186,441, 2012 | 7 | 2012 |
| A cluster-based human resources analytics for predicting employee turnover using optimized Artificial Neural Networks and data augmentation MR Shafie, H Khosravi, S Farhadpour, S Das, I Ahmed Decision Analytics Journal 11, 100461, 2024 | 6 | 2024 |
| Learning low-precision structured subnetworks using joint layerwise channel pruning and uniform quantization X Zhang, I Colbert, S Das Applied Sciences 12 (15), 7829, 2022 | 6 | 2022 |
| An energy-efficient edge computing paradigm for convolution-based image upsampling I Colbert, K Kreutz-Delgado, S Das IEEE Access 9, 147967-147984, 2021 | 6 | 2021 |
| Event-driven contrastive divergence: neural sampling foundations E Neftci, S Das, B Pedroni, K Kreutz-Delgado, G Cauwenberghs Frontiers in neuroscience 9, 137471, 2015 | 6 | 2015 |
Ian ColbertAdvanced Micro Devices (AMD)在 amd.com 的电子邮件经过验证
