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2020 – today
- 2024
- [j36]Andrea Soltoggio
, Eseoghene Ben-Iwhiwhu
A collective AI via lifelong learning and sharing at the edge. Nat. Mac. Intell. 6(3): 251-264 (2024) - [j35]Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Do we really need a large number of visual prompts? Neural Networks 177: 106390 (2024) - [j34]Abhishek Moitra
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. IEEE Trans. Emerg. Top. Comput. Intell. 8(2): 2101-2111 (2024) - [j33]Ruokai Yin
Workload-Balanced Pruning for Sparse Spiking Neural Networks. IEEE Trans. Emerg. Top. Comput. Intell. 8(4): 2897-2907 (2024) - [c46]Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda:
MINT: Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks. ASPDAC 2024: 830-835 - [c45]Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda:
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. DATE 2024: 1-6 - [c44]Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
HaLo-FL: Hardware-Aware Low-Precision Federated Learning. DATE 2024: 1-6 - [c43]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. ICASSP 2024: 13311-13315 - [i89]Donghyun Lee, Ruokai Yin, Youngeun Kim, Abhishek Moitra, Yuhang Li, Priyadarshini Panda:
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training. CoRR abs/2401.08001 (2024) - [i88]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation. CoRR abs/2402.02586 (2024) - [i87]Youngeun Kim, Yuhang Li, Priyadarshini Panda:
One-stage Prompt-based Continual Learning. CoRR abs/2402.16189 (2024) - [i86]Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda:
PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference. CoRR abs/2404.15185 (2024) - [i85]Ruokai Yin, Youngeun Kim, Di Wu, Priyadarshini Panda:
LoAS: Fully Temporal-Parallel Datatflow for Dual-Sparse Spiking Neural Networks. CoRR abs/2407.14073 (2024) - [i84]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
TReX- Reusing Vision Transformer's Attention for Efficient Xbar-based Computing. CoRR abs/2408.12742 (2024) - [i83]Abhishek Moitra, Abhiroop Bhattacharjee, Yuhang Li, Youngeun Kim, Priyadarshini Panda:
When In-memory Computing Meets Spiking Neural Networks - A Perspective on Device-Circuit-System-and-Algorithm Co-design. CoRR abs/2408.12767 (2024) - [i82]Shiting Xiao, Yuhang Li, Youngeun Kim, Donghyun Lee, Priyadarshini Panda:
ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition. CoRR abs/2409.01564 (2024) - [i81]Donghyun Lee, Yuhang Li, Youngeun Kim, Shiting Xiao, Priyadarshini Panda:
Spiking Transformer with Spatial-Temporal Attention. CoRR abs/2409.19764 (2024) - 2023
- [j32]Nitin Rathi
Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware. ACM Comput. Surv. 55(12): 243:1-243:49 (2023) - [j31]Jason K. Eshraghian
Guest Editorial Dynamical Neuro-AI Learning Systems: Devices, Circuits, Architecture and Algorithms. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 873-876 (2023) - [j30]Abhiroop Bhattacharjee
HyDe: A brid PCM/FeFET/SRAM vice-Search for Optimizing Area and Energy-Efficiencies in Analog IMC Platforms. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 1073-1082 (2023) - [j29]Robert Legenstein
Editorial: Focus on algorithms for neuromorphic computing. Neuromorph. Comput. Eng. 3(3): 30402 (2023) - [j28]Yeshwanth Venkatesha
Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems. Neural Networks 168: 569-579 (2023) - [j27]Ruokai Yin
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(6): 1926-1938 (2023) - [j26]Abhishek Moitra
SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(11): 3815-3828 (2023) - [j25]Abhiroop Bhattacharjee
XploreNAS: Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars. ACM Trans. Embed. Comput. Syst. 22(4): 62:1-62:17 (2023) - [j24]Yuhang Li, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda:
Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient. Trans. Mach. Learn. Res. 2023 (2023) - [j23]Abhiroop Bhattacharjee
SwitchX: Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars. ACM Trans. Design Autom. Electr. Syst. 28(4): 60:1-60:21 (2023) - [c42]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Anna Hambitzer, Priyadarshini Panda:
Exploring Temporal Information Dynamics in Spiking Neural Networks. AAAI 2023: 8308-8316 - [c41]Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract). ACSSC 2023: 543-544 - [c40]Yuhang Li, Abhishek Moitra, Tamar Geller, Priyadarshini Panda:
Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing. DAC 2023: 1-6 - [c39]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. DAC 2023: 1-6 - [c38]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. DATE 2023: 1-6 - [c37]Abhishek Moitra
Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing. ACM Great Lakes Symposium on VLSI 2023: 137-138 - [c36]Abhiroop Bhattacharjee
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. ACM Great Lakes Symposium on VLSI 2023: 619-624 - [c35]Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda:
SEENN: Towards Temporal Spiking Early Exit Neural Networks. NeurIPS 2023 - [i80]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. CoRR abs/2302.04712 (2023) - [i79]Ruokai Yin, Youngeun Kim, Yuhang Li, Abhishek Moitra, Nitin Satpute, Anna Hambitzer, Priyadarshini Panda:
Workload-Balanced Pruning for Sparse Spiking Neural Networks. CoRR abs/2302.06746 (2023) - [i78]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars. CoRR abs/2302.07769 (2023) - [i77]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. CoRR abs/2303.17646 (2023) - [i76]Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda:
SEENN: Towards Temporal Spiking Early-Exit Neural Networks. CoRR abs/2304.01230 (2023) - [i75]Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - [i74]Yuhang Li, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda:
Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient. CoRR abs/2304.13098 (2023) - [i73]Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda:
Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems. CoRR abs/2305.07135 (2023) - [i72]Ruokai Yin, Yuhang Li, Abhishek Moitra, Priyadarshini Panda:
MINT: Multiplier-less Integer Quantization for Spiking Neural Networks. CoRR abs/2305.09850 (2023) - [i71]Youngeun Kim, Yuhang Li, Abhishek Moitra, Priyadarshini Panda:
Do We Really Need a Large Number of Visual Prompts? CoRR abs/2305.17223 (2023) - [i70]Yuhang Li, Abhishek Moitra, Tamar Geller, Priyadarshini Panda:
Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing. CoRR abs/2305.17346 (2023) - [i69]Youngeun Kim, Yuhang Li, Abhishek Moitra, Ruokai Yin, Priyadarshini Panda:
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks. CoRR abs/2305.18360 (2023) - [i68]Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda:
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. CoRR abs/2305.18416 (2023) - [i67]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms. CoRR abs/2308.00664 (2023) - [i66]Qian Zhang, Chenxi Wu, Adar Kahana, Youngeun Kim, Yuhang Li, George Em Karniadakis, Priyadarshini Panda:
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning. CoRR abs/2308.16372 (2023) - [i65]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. CoRR abs/2309.03388 (2023) - [i64]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. CoRR abs/2310.06845 (2023) - [i63]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory. CoRR abs/2312.03559 (2023) - [i62]Yuhang Li, Youngeun Kim, Donghyun Lee, Priyadarshini Panda:
StableQ: Enhancing Data-Scarce Quantization with Text-to-Image Data. CoRR abs/2312.05272 (2023) - 2022
- [j22]Dennis V. Christensen
2022 roadmap on neuromorphic computing and engineering. Neuromorph. Comput. Eng. 2(2): 22501 (2022) - [j21]Youngeun Kim
Beyond classification: directly training spiking neural networks for semantic segmentation. Neuromorph. Comput. Eng. 2(4): 44015 (2022) - [j20]Rachel Sterneck
Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(5): 1423-1435 (2022) - [j19]Abhiroop Bhattacharjee
NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(8): 2625-2637 (2022) - [c34]Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda:
PrivateSNN: Privacy-Preserving Spiking Neural Networks. AAAI 2022: 1192-1200 - [c33]Abhiroop Bhattacharjee
MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning. DAC 2022: 499-504 - [c32]Youngeun Kim, Hyunsoo Kim
Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar. DATE 2022: 1111-1114 - [c31]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda:
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. DATE 2022: 1119-1122 - [c30]Youngeun Kim
Neural Architecture Search for Spiking Neural Networks. ECCV (24) 2022: 36-56 - [c29]Youngeun Kim
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. ECCV (12) 2022: 102-120 - [c28]Yuhang Li
Neuromorphic Data Augmentation for Training Spiking Neural Networks. ECCV (7) 2022: 631-649 - [c27]Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda:
Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? ICASSP 2022: 71-75 - [c26]Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda, Arijit Raychowdhury, Kaushik Roy:
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning. ICRA 2022: 7492-7498 - [c25]Abhiroop Bhattacharjee
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. ISLPED 2022: 1:1-1:6 - [i61]Youngeun Kim, Hyunsoo Kim, Seijoon Kim, Sang Joon Kim, Priyadarshini Panda:
Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar. CoRR abs/2201.01479 (2022) - [i60]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda:
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. CoRR abs/2201.05229 (2022) - [i59]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Priyadarshini Panda:
Neural Architecture Search for Spiking Neural Networks. CoRR abs/2201.10355 (2022) - [i58]Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda:
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks? CoRR abs/2202.03133 (2022) - [i57]Abhishek Moitra, Youngeun Kim, Priyadarshini Panda:
Adversarial Detection without Model Information. CoRR abs/2202.04271 (2022) - [i56]Yuhang Li, Youngeun Kim, Hyoungseob Park, Tamar Geller, Priyadarshini Panda:
Neuromorphic Data Augmentation for Training Spiking Neural Networks. CoRR abs/2203.06145 (2022) - [i55]Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park, Yuhang Li, Priyadarshini Panda:
Addressing Client Drift in Federated Continual Learning with Adaptive Optimization. CoRR abs/2203.13321 (2022) - [i54]Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda:
MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning. CoRR abs/2204.05274 (2022) - [i53]Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. CoRR abs/2204.05422 (2022) - [i52]Abhiroop Bhattacharjee, Youngeun Kim, Abhishek Moitra, Priyadarshini Panda:
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. CoRR abs/2206.09599 (2022) - [i51]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda:
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. CoRR abs/2207.01382 (2022) - [i50]Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda:
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. CoRR abs/2210.12899 (2022) - [i49]Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Anna Hambitzer, Priyadarshini Panda:
Exploring Temporal Information Dynamics in Spiking Neural Networks. CoRR abs/2211.14406 (2022) - [i48]Yuhang Li, Ruokai Yin, Hyoungseob Park, Youngeun Kim, Priyadarshini Panda:
Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks. CoRR abs/2212.02233 (2022) - 2021
- [j18]Priyadarshini Panda
Implicit adversarial data augmentation and robustness with Noise-based Learning. Neural Networks 141: 120-132 (2021) - [j17]Youngeun Kim
Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing. Neural Networks 144: 686-698 (2021) - [j16]Youngeun Kim
Domain Adaptation Without Source Data. IEEE Trans. Artif. Intell. 2(6): 508-518 (2021) - [j15]Abhishek Moitra
DetectX - Adversarial Input Detection Using Current Signatures in Memristive XBar Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. 68(11): 4482-4494 (2021) - [j14]Yeshwanth Venkatesha
Federated Learning With Spiking Neural Networks. IEEE Trans. Signal Process. 69: 6183-6194 (2021) - [c24]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. DATE 2021: 884-889 - [c23]Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. DATE 2021: 1360-1365 - [i47]Rachel Sterneck, Abhishek Moitra, Priyadarshini Panda:
Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks. CoRR abs/2101.01543 (2021) - [i46]Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. CoRR abs/2101.04354 (2021) - [i45]Youngeun Kim, Priyadarshini Panda:
Visual Explanations from Spiking Neural Networks using Interspike Intervals. CoRR abs/2103.14441 (2021) - [i44]Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda:
PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks. CoRR abs/2104.03414 (2021) - [i43]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. CoRR abs/2105.04003 (2021) - [i42]Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill
2021 Roadmap on Neuromorphic Computing and Engineering. CoRR abs/2105.05956 (2021) - [i41]Yeshwanth Venkatesha, Youngeun Kim, Leandros Tassiulas, Priyadarshini Panda:
Federated Learning with Spiking Neural Networks. CoRR abs/2106.06579 (2021) - [i40]Abhishek Moitra, Priyadarshini Panda:
DetectX - Adversarial Input Detection using Current Signatures in Memristive XBar Arrays. CoRR abs/2106.12021 (2021) - [i39]Adarsh Kumar Kosta, Malik Aqeel Anwar, Priyadarshini Panda, Arijit Raychowdhury, Kaushik Roy:
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning. CoRR abs/2109.08231 (2021) - [i38]Youngeun Kim, Joshua Chough, Priyadarshini Panda:
Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation. CoRR abs/2110.07742 (2021) - 2020
- [j13]Isha Garg
A Low Effort Approach to Structured CNN Design Using PCA. IEEE Access 8: 1347-1360 (2020) - [j12]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning. Neural Networks 121: 148-160 (2020) - [c22]Saima Sharmin
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-linear Activations. ECCV (29) 2020: 399-414 - [c21]Gopalakrishnan Srinivasan
Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing. ICASSP 2020: 8549-8553 - [c20]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. ICLR 2020 - [c19]Timothy Foldy-Porto, Yeshwanth Venkatesha, Priyadarshini Panda:
Activation Density Driven Efficient Pruning in Training. ICPR 2020: 8929-8936 - [c18]Aosong Feng, Priyadarshini Panda:
Energy-efficient and Robust Cumulative Training with Net2Net Transformation. IJCNN 2020: 1-7 - [c17]Krishna Reddy Kesari, Priyadarshini Panda, Gopalakrishnan Srinivasan
Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity. IJCNN 2020: 1-8 - [c16]Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks. IJCNN 2020: 1-7 - [c15]Priyadarshini Panda:
QUANOS: adversarial noise sensitivity driven hybrid quantization of neural networks. ISLPED 2020: 187-192 - [c14]Priyadarshini Panda, Kaushik Roy:
Invited Talk: Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems. VLSID 2020: 1-18 - [i37]Timothy Foldy-Porto, Priyadarshini Panda:
Activation Density driven Energy-Efficient Pruning in Training. CoRR abs/2002.02949 (2020) - [i36]Sai Aparna Aketi, Priyadarshini Panda, Kaushik Roy:
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors. CoRR abs/2002.11052 (2020) - [i35]Aosong Feng, Priyadarshini Panda:
Energy-efficient and Robust Cumulative Training with Net2Net Transformation. CoRR abs/2003.01204 (2020) - [i34]Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan:
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks. CoRR abs/2003.02800 (2020) - [i33]Saima Sharmin, Nitin Rathi, Priyadarshini Panda, Kaushik Roy:
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations. CoRR abs/2003.10399 (2020) - [i32]Priyadarshini Panda:
QUANOS- Adversarial Noise Sensitivity Driven Hybrid Quantization of Neural Networks. CoRR abs/2004.11233 (2020) - [i31]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. CoRR abs/2005.01807 (2020) - [i30]Youngeun Kim, Sungeun Hong, Donghyeon Cho, Hyoungseob Park, Priyadarshini Panda:
Domain Adaptation without Source Data. CoRR abs/2007.01524 (2020) - [i29]Abhiroop Bhattacharjee, Priyadarshini Panda:
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks. CoRR abs/2008.11298 (2020) - [i28]Varigonda Pavan Teja, Priyadarshini Panda:
Compression-aware Continual Learning using Singular Value Decomposition. CoRR abs/2009.01956 (2020) - [i27]Youngeun Kim, Priyadarshini Panda:
Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch. CoRR abs/2010.01729 (2020) - [i26]Abhishek Moitra, Priyadarshini Panda:
Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks. CoRR abs/2011.13392 (2020) - [i25]Abhiroop Bhattacharjee, Priyadarshini Panda:
SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars. CoRR abs/2011.14498 (2020) - [i24]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Youngeun Kim, Priyadarshini Panda:
NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars. CoRR abs/2012.00261 (2020)
2010 – 2019
- 2019
- [j11]Priyadarshini Panda
Discretization Based Solutions for Secure Machine Learning Against Adversarial Attacks. IEEE Access 7: 70157-70168 (2019) - [j10]Yinghan Long
Structured Learning for Action Recognition in Videos. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(3): 475-484 (2019) - [j9]Chankyu Lee
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity. IEEE Trans. Cogn. Dev. Syst. 11(3): 384-394 (2019) - [j8]Nitin Rathi
STDP-Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy-Efficient Recognition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(4): 668-677 (2019) - [j7]Baibhab Chatterjee
Exploiting Inherent Error Resiliency of Deep Neural Networks to Achieve Extreme Energy Efficiency Through Mixed-Signal Neurons. IEEE Trans. Very Large Scale Integr. Syst. 27(6): 1365-1377 (2019) - [c13]Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy:
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis. IJCNN 2019: 1-8 - [c12]Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar, Chankyu Lee, Wachirawit Ponghiran, Kaushik Roy:
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks. IJCNN 2019: 1-8 - [c11]Deboleena Roy, Gopalakrishnan Srinivasan
Neural Networks at the Edge. SMARTCOMP 2019: 45-50 - [i23]Priyadarshini Panda, Indranil Chakraborty, Kaushik Roy:
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks. CoRR abs/1902.03151 (2019) - [i22]Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar, Chankyu Lee, Wachirawit Ponghiran, Kaushik Roy:
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks. CoRR abs/1905.02704 (2019) - [i21]Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy:
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis. CoRR abs/1905.03219 (2019) - [i20]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation. CoRR abs/1906.08861 (2019) - [i19]Priyadarshini Panda, Sai Aparna Aketi
Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization. CoRR abs/1910.13931 (2019) - 2018
- [j6]Priyadarshini Panda
ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural Networks. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 51-64 (2018) - [j5]Syed Shakib Sarwar
Energy Efficient Neural Computing: A Study of Cross-Layer Approximations. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 796-809 (2018) - [j4]Gopalakrishnan Srinivasan
STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing. ACM J. Emerg. Technol. Comput. Syst. 14(4): 44:1-44:12 (2018) - [i18]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Tree-CNN: A Deep Convolutional Neural Network for Lifelong Learning. CoRR abs/1802.05800 (2018) - [i17]Baibhab Chatterjee, Priyadarshini Panda, Shovan Maity, Ayan Biswas, Kaushik Roy, Shreyas Sen:
Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons. CoRR abs/1806.05141 (2018) - [i16]Priyadarshini Panda, Kaushik Roy:
Explainable Learning: Implicit Generative Modelling during Training for Adversarial Robustness. CoRR abs/1807.02188 (2018) - [i15]Isha Garg, Priyadarshini Panda, Kaushik Roy:
A Low Effort Approach to Structured CNN Design Using PCA. CoRR abs/1812.06224 (2018) - 2017
- [j3]Priyadarshini Panda
Energy-Efficient and Improved Image Recognition with Conditional Deep Learning. ACM J. Emerg. Technol. Comput. Syst. 13(3): 33:1-33:21 (2017) - [j2]Priyadarshini Panda
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(12): 2017-2029 (2017) - [j1]Priyadarshini Panda
Energy-Efficient Object Detection Using Semantic Decomposition. IEEE Trans. Very Large Scale Integr. Syst. 25(9): 2673-2677 (2017) - [c10]Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda, Kaushik Roy:
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks. DAC 2017: 27:1-27:6 - [c9]Priyadarshini Panda, Kaushik Roy:
Semantic driven hierarchical learning for energy-efficient image classification. DATE 2017: 1582-1587 - [c8]Maryam Parsa, Priyadarshini Panda, Shreyas Sen, Kaushik Roy:
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis. EMBC 2017: 78-81 - [c7]Baibhab Chatterjee
An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems. ICRC 2017: 1-2 - [c6]Priyadarshini Panda, Gopalakrishnan Srinivasan
EnsembleSNN: Distributed assistive STDP learning for energy-efficient recognition in spiking neural networks. IJCNN 2017: 2629-2635 - [c5]Syed Shakib Sarwar, Priyadarshini Panda, Kaushik Roy:
Gabor filter assisted energy efficient fast learning Convolutional Neural Networks. ISLPED 2017: 1-6 - [i14]Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda, Kaushik Roy:
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks. CoRR abs/1702.06064 (2017) - [i13]Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy:
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks. CoRR abs/1703.03854 (2017) - [i12]Priyadarshini Panda, Jason M. Allred, Shriram Ramanathan, Kaushik Roy:
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks. CoRR abs/1703.07655 (2017) - [i11]Syed Shakib Sarwar, Priyadarshini Panda, Kaushik Roy:
Gabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks. CoRR abs/1705.04748 (2017) - [i10]Nitin Rathi, Priyadarshini Panda, Kaushik Roy:
STDP Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy Efficient Recognition. CoRR abs/1710.04734 (2017) - [i9]Priyadarshini Panda, Narayan Srinivasa:
Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model. CoRR abs/1710.07354 (2017) - [i8]Baibhab Chatterjee, Priyadarshini Panda, Shovan Maity, Kaushik Roy, Shreyas Sen:
An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems. CoRR abs/1710.09012 (2017) - [i7]Priyadarshini Panda, Kaushik Roy:
Chaos-guided Input Structuring for Improved Learning in Recurrent Neural Networks. CoRR abs/1712.09206 (2017) - 2016
- [c4]Priyadarshini Panda, Abhronil Sengupta, Syed Shakib Sarwar, Gopalakrishnan Srinivasan
Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems. DAC 2016: 98:1-98:6 - [c3]Priyadarshini Panda, Abhronil Sengupta, Kaushik Roy:
Conditional Deep Learning for energy-efficient and enhanced pattern recognition. DATE 2016: 475-480 - [c2]Priyadarshini Panda, Kaushik Roy:
Unsupervised regenerative learning of hierarchical features in Spiking Deep Networks for object recognition. IJCNN 2016: 299-306 - [c1]Abhronil Sengupta, Priyadarshini Panda, Anand Raghunathan
Neuromorphic Computing Enabled by Spin-Transfer Torque Devices. VLSID 2016: 32-37 - [i6]Priyadarshini Panda, Kaushik Roy:
Unsupervised Regenerative Learning of Hierarchical Features in Spiking Deep Networks for Object Recognition. CoRR abs/1602.01510 (2016) - [i5]Priyadarshini Panda, Kaushik Roy:
Attention Tree: Learning Hierarchies of Visual Features for Large-Scale Image Recognition. CoRR abs/1608.00611 (2016) - [i4]Priyadarshini Panda, Aayush Ankit, Parami Wijesinghe, Kaushik Roy:
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition. CoRR abs/1609.03396 (2016) - 2015
- [i3]Priyadarshini Panda, Abhronil Sengupta, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy:
Object Detection using Semantic Decomposition for Energy-Efficient Neural Computing. CoRR abs/1509.08970 (2015) - [i2]Priyadarshini Panda, Abhronil Sengupta, Kaushik Roy:
Conditional Deep Learning for Energy-Efficient and Enhanced Pattern Recognition. CoRR abs/1509.08971 (2015) - [i1]Abhronil Sengupta, Priyadarshini Panda, Parami Wijesinghe, Yusung Kim, Kaushik Roy:
Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons. CoRR abs/1510.00440 (2015)
Coauthor Index
[j35] [j34] [j33] [c45] [i89] [i87] [i85] [i84] [i83] [i82] [i81] [j28] [j27] [j24] [c42] [c39] [c36] [c35] [i79] [i77] [i76] [i74] [i73] [i71] [i69] [i68] [i66] [i64] [i62] [j22] [j21] [j19] [c34] [c32] [c30] [c29] [c28] [c27] [c25] [i61] [i59] [i58] [i57] [i56] [i55] [i53] [i52] [i51] [i49] [i48] [j17] [j16] [j14] [i45] [i44] [i42] [i41] [i38] [i30] [i27] [i24]
[j35] [j34] [j33] [c46] [c45] [c44] [c43] [i89] [i88] [i86] [i84] [i83] [j30] [j27] [j26] [j25] [c41] [c40] [c39] [c38] [c37] [c36] [i80] [i79] [i78] [i77] [i72] [i71] [i70] [i69] [i68] [i67] [i65] [i64] [i63] [j20] [c33] [c27] [c25] [i58] [i57] [i54] [i53] [i52] [i50] [j15] [c24] [c23] [i47] [i46] [i43] [i40] [i26]
[j36] [j32] [c26] [j18] [i39] [j13] [j12] [c22] [c21] [c20] [c17] [c14] [i36] [i33] [i31] [j11] [j10] [j9] [j8] [j7] [c13] [c12] [c11] [i23] [i22] [i21] [i20] [i19] [j6] [j5] [j4] [i18] [i17] [i16] [i15] [j3] [j2] [j1] [c10] [c9] [c8] [c7] [c6] [c5] [i14] [i13] [i12] [i11] [i10] [i8] [i7] [c4] [c3] [c2] [c1] [i6] [i5] [i4] [i3] [i2] [i1]
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