Priyadarshini Panda
Orcid: 0000-0002-4167-6782
According to our database1,
Priyadarshini Panda
authored at least 115 papers
between 2015 and 2024.
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Bibliography
2024
IEEE Trans. Emerg. Top. Comput. Intell., April, 2024
ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation.
CoRR, 2024
CoRR, 2024
2023
Guest Editorial Dynamical Neuro-AI Learning Systems: Devices, Circuits, Architecture and Algorithms.
IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2023
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., December, 2023
Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware.
ACM Comput. Surv., December, 2023
SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., November, 2023
Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems.
Neural Networks, November, 2023
Neuromorph. Comput. Eng., September, 2023
<i>SwitchX</i>: Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars.
ACM Trans. Design Autom. Electr. Syst., July, 2023
<i>XploreNAS</i>: Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars.
ACM Trans. Embed. Comput. Syst., July, 2023
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., June, 2023
Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient.
Trans. Mach. Learn. Res., 2023
MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory.
CoRR, 2023
CoRR, 2023
HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms.
CoRR, 2023
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks.
CoRR, 2023
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking.
CoRR, 2023
XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Hardware Accelerators for Spiking Neural Networks for Energy-Efficient Edge Computing.
Proceedings of the Great Lakes Symposium on VLSI 2023, 2023
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing.
Proceedings of the Great Lakes Symposium on VLSI 2023, 2023
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023
XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Beyond classification: directly training spiking neural networks for semantic segmentation.
Neuromorph. Comput. Eng., December, 2022
Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022
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., 2022
Neuromorph. Comput. Eng., 2022
Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks.
CoRR, 2022
CoRR, 2022
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars.
Proceedings of the ISLPED '22: ACM/IEEE International Symposium on Low Power Electronics and Design, Boston, MA, USA, August 1, 2022
RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022
Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks?
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the Computer Vision, 2022
Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022
MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
DetectX - Adversarial Input Detection Using Current Signatures in Memristive XBar Arrays.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021
Neural Networks, 2021
Neural Networks, 2021
CoRR, 2021
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
2020
Neural Networks, 2020
NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars.
CoRR, 2020
SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars.
CoRR, 2020
Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks.
CoRR, 2020
Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch.
CoRR, 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks.
CoRR, 2020
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors.
CoRR, 2020
Invited Talk: Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems.
Proceedings of the 33rd International Conference on VLSI Design and 19th International Conference on Embedded Systems, 2020
Proceedings of the ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 25th International Conference on Pattern Recognition, 2020
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation.
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-linear Activations.
Proceedings of the Computer Vision - ECCV 2020, 2020
2019
Exploiting Inherent Error Resiliency of Deep Neural Networks to Achieve Extreme Energy Efficiency Through Mixed-Signal Neurons.
IEEE Trans. Very Large Scale Integr. Syst., 2019
STDP-Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy-Efficient Recognition.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity.
IEEE Trans. Cogn. Dev. Syst., 2019
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019
Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization.
CoRR, 2019
Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation.
CoRR, 2019
Discretization Based Solutions for Secure Machine Learning Against Adversarial Attacks.
IEEE Access, 2019
Proceedings of the IEEE International Conference on Smart Computing, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis.
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing.
ACM J. Emerg. Technol. Comput. Syst., 2018
IEEE J. Emerg. Sel. Topics Circuits Syst., 2018
ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural Networks.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2018
Explainable Learning: Implicit Generative Modelling during Training for Adversarial Robustness.
CoRR, 2018
Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons.
CoRR, 2018
2017
IEEE Trans. Very Large Scale Integr. Syst., 2017
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017
ACM J. Emerg. Technol. Comput. Syst., 2017
CoRR, 2017
Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model.
CoRR, 2017
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks.
CoRR, 2017
Proceedings of the 2017 IEEE/ACM International Symposium on Low Power Electronics and Design, 2017
EnsembleSNN: Distributed assistive STDP learning for energy-efficient recognition in spiking neural networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems.
Proceedings of the IEEE International Conference on Rebooting Computing, 2017
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017
RESPARC: A Reconfigurable and Energy-Efficient Architecture with Memristive Crossbars for Deep Spiking Neural Networks.
Proceedings of the 54th Annual Design Automation Conference, 2017
2016
Attention Tree: Learning Hierarchies of Visual Features for Large-Scale Image Recognition.
CoRR, 2016
Proceedings of the 29th International Conference on VLSI Design and 15th International Conference on Embedded Systems, 2016
Unsupervised regenerative learning of hierarchical features in Spiking Deep Networks for object recognition.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016
Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems.
Proceedings of the 53rd Annual Design Automation Conference, 2016
2015
CoRR, 2015