PhICNet: Physics-Incorporated Convolutional Recurrent Neural Networks for Modeling Dynamical Systems P Saha, S Dash, S Mukhopadhyay arXiv preprint arXiv:2004.06243, 2020 | 37* | 2020 |
Sequence approximation using feedforward spiking neural network for spatiotemporal learning: Theory and optimization methods X She, S Dash, S Mukhopadhyay International Conference on Learning Representations, 2021 | 26 | 2021 |
Aya 23: Open Weight Releases to Further Multilingual Progress V Aryabumi, J Dang, D Talupuru, S Dash, D Cairuz, H Lin, B Venkitesh, ... Arxiv preprint, 2024 | 23 | 2024 |
Intriguing Properties of Quantization at Scale A Ahmadian*, S Dash*, H Chen*, B Venkitesh, S Gou, P Blunsom, ... Advances in Neural Information Processing Systems, 2023 | 23 | 2023 |
A heterogeneous spiking neural network for unsupervised learning of spatiotemporal patterns X She, S Dash, D Kim, S Mukhopadhyay Frontiers in Neuroscience 14, 615756, 2021 | 23 | 2021 |
Robust processing-in-memory with multibit ReRAM using Hessian-driven mixed-precision computation S Dash, Y Luo, A Lu, S Yu, S Mukhopadhyay IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2021 | 18 | 2021 |
Hessian-driven unequal protection of dnn parameters for robust inference S Dash, S Mukhopadhyay Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020 | 10 | 2020 |
Low power implantable spike sorting scheme based on neuromorphic classifier with supervised training engine R Pathak, S Dash, AK Mukhopadhyay, A Basu, M Sharad 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 266-271, 2017 | 10 | 2017 |
Characterization of drain current variations in fefets for pim-based dnn accelerators NE Miller, Z Wang, S Dash, AI Khan, S Mukhopadhyay 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits …, 2021 | 9 | 2021 |
Learning point processes using recurrent graph network S Dash, X She, S Mukhopadhyay 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 6 | 2022 |
Reliable edge intelligence in unreliable environment M Lee, X She, B Chakraborty, S Dash, B Mudassar, S Mukhopadhyay 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 896-901, 2021 | 6 | 2021 |
Unsupervised hebbian learning on point sets in starcraft ii B Kang, H Kumar, S Dash, S Mukhopadhyay 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |
Low cost autonomous navigation and control of a mechanically balanced bicycle with dual locomotion mode A Pandey, S Mahajan, A Kosta, D Yadav, V Pandey, S Sahay, S Jha, ... 2015 IEEE International Transportation Electrification Conference (ITEC), 1-10, 2015 | 5 | 2015 |
Associative memory augmented asynchronous spatiotemporal representation learning for event-based perception U Kamal*, S Dash*, S Mukhopadhyay The Eleventh International Conference on Learning Representations, 2022 | 4 | 2022 |
A flexible precision multi-format in-memory vector matrix multiplication engine in 65 nm cmos with rf machine learning support M Mukherjee, Y Long, J Woo, D Kim, NM Rahman, S Dash, ... IEEE Solid-State Circuits Letters 3, 450-453, 2020 | 3 | 2020 |
Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs D Paglieri, S Dash, T Rocktäschel, J Parker-Holder arXiv preprint arXiv:2405.20835, 2024 | 2 | 2024 |
Brain-Inspired Spatiotemporal Processing Algorithms for Efficient Event-Based Perception B Chakraborty, U Kamal, X She, S Dash, S Mukhopadhyay 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2023 | 1 | 2023 |
How Does Quantization Affect Multilingual LLMs? K Marchisio, S Dash, H Chen, D Aumiller, A Üstün, S Hooker, S Ruder arXiv preprint arXiv:2407.03211, 2024 | | 2024 |
Impact of HKMG and FDSOI FeFET drain current variation in processing-in-memory architectures NE Miller, Z Wang, S Dash, AI Khan, S Mukhopadhyay Journal of Materials Research 36, 4379-4393, 2021 | | 2021 |