Priyadarshini Panda

发表

STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing

Kaushik Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2018, ACM J. Emerg. Technol. Comput. Syst..

Synthesizing Images From Spatio-Temporal Representations Using Spike-Based Backpropagation

Priyadarshini Panda, Deboleena Roy, Kaushik Roy, 2019, Front. Neurosci..

Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks pdf

Priyadarshini Panda, Karina Vasquez, Yeshwanth Venkatesha, 2021, 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).

NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars pdf

Priyadarshini Panda, Abhiroop Bhattacharjee, Lakshya Bhatnagar, 2020, ArXiv.

Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks pdf

Kaushik Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2017, ArXiv.

Implicit Generative Modeling of Random Noise during Training for Adversarial Robustness

Priyadarshini Panda, Kaushik Roy, 2018 .

Exploiting Inherent Error Resiliency of Deep Neural Networks to Achieve Extreme Energy Efficiency Through Mixed-Signal Neurons

Kaushik Roy, Shreyas Sen, Priyadarshini Panda, 2019, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

An Energy-Efficient Mixed-Signal Neuron for Inherently Error-Resilient Neuromorphic Systems

Kaushik Roy, Shreyas Sen, Priyadarshini Panda, 2017, 2017 IEEE International Conference on Rebooting Computing (ICRC).

Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors pdf

Kaushik Roy, Priyadarshini Panda, Sai Aparna Aketi, 2020, ArXiv.

Invited — Cross-layer approximations for neuromorphic computing: From devices to circuits and systems

Kaushik Roy, Anand Raghunathan, Swagath Venkataramani, 2016, 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC).

Progressive Domain Adaptation from a Source Pre-trained Model.

Sungeun Hong, Priyadarshini Panda, Youngeun Kim, 2020 .

Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity

Gopalakrishnan Srinivasan, Priyadarshini Panda, Chankyu Lee, 2019, IEEE Transactions on Cognitive and Developmental Systems.

RESPARC: A reconfigurable and energy-efficient architecture with Memristive Crossbars for deep Spiking Neural Networks

Kaushik Roy, Priyadarshini Panda, Abhronil Sengupta, 2017, 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC).

Invited Talk: Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems

Kaushik Roy, Priyadarshini Panda, 2020, VLSI Design.

Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis

Priyadarshini Panda, Kaushik Roy, Efstathia Soufleri, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Towards spike-based machine intelligence with neuromorphic computing

Kaushik Roy, Priyadarshini Panda, Akhilesh Jaiswal, 2019, Nature.

Structured Learning for Action Recognition in Videos

Kaushik Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2019, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

Correction: Corrigendum: Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons

Parami Wijesinghe, Priyadarshini Panda, Abhronil Sengupta, 2017, Scientific reports.

Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks pdf

Priyadarshini Panda, Abhishek Moitra, 2020, ArXiv.

Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons

Kaushik Roy, Parami Wijesinghe, Priyadarshini Panda, 2015, Scientific Reports.

Domain Adaptation without Source Data pdf

Sungeun Hong, Priyadarshini Panda, Donghyeon Cho, 2020, ArXiv.

SpiLinC: Spiking Liquid-Ensemble Computing for Unsupervised Speech and Image Recognition

Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy, 2018, Front. Neurosci..

Semantic driven hierarchical learning for energy-efficient image classification

Kaushik Roy, Priyadarshini Panda, 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.

Activation Density driven Energy-Efficient Pruning in Training pdf

Priyadarshini Panda, Timothy Foldy-Porto, P. Panda, 2020, ArXiv.

Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons pdf

Kaushik Roy, Shreyas Sen, Priyadarshini Panda, 2018, ArXiv.

Chaos-guided Input Structuring for Improved Learning in Recurrent Neural Networks pdf

Kaushik Roy, Priyadarshini Panda, K. Roy, 2017, ArXiv.

STDP-Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy-Efficient Recognition

Kaushik Roy, Priyadarshini Panda, Nitin Rathi, 2017, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Training Deep Spiking Convolutional Neural Networks With STDP-Based Unsupervised Pre-training Followed by Supervised Fine-Tuning

Gopalakrishnan Srinivasan, Priyadarshini Panda, Chankyu Lee, 2018, Front. Neurosci..

Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning

Priyadarshini Panda, Kaushik Roy, Deboleena Roy, 2018, Neural Networks.

Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks

Priyadarshini Panda, Kaushik Roy, K. Roy, 2017, Front. Neurosci..

Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations

Kaushik Roy, Priyadarshini Panda, Saima Sharmin, 2020, ECCV.

Unsupervised regenerative learning of hierarchical features in Spiking Deep Networks for object recognition

Kaushik Roy, Priyadarshini Panda, K. Roy, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Object Detection using Semantic Decomposition for Energy-Efficient Neural Computing pdf

Kaushik Roy, Anand Raghunathan, Swagath Venkataramani, 2015, ArXiv.

EnsembleSNN: Distributed assistive STDP learning for energy-efficient recognition in spiking neural networks

Kaushik Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Conditional Deep Learning for energy-efficient and enhanced pattern recognition

Kaushik Roy, Priyadarshini Panda, Abhronil Sengupta, 2015, 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Energy-efficient and Robust Cumulative Training with Net2Net Transformation

Priyadarshini Panda, Aosong Feng, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks

Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Organismic materials for beyond von Neumann machines

Kai Wang, Yoav Kalcheim, Ivan K. Schuller, 2020 .

QUANOS: adversarial noise sensitivity driven hybrid quantization of neural networks

Priyadarshini Panda, 2020, ISLPED.

Attention Tree: Learning Hierarchies of Visual Features for Large-Scale Image Recognition pdf

Kaushik Roy, Priyadarshini Panda, K. Roy, 2016, ArXiv.

A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks

Priyadarshini Panda, Chankyu Lee, Kaushik Roy, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition

Parami Wijesinghe, Kaushik Roy, Priyadarshini Panda, 2016, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars pdf

Priyadarshini Panda, Abhiroop Bhattacharjee, 2020, ArXiv.

Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis

Kaushik Roy, Shreyas Sen, Priyadarshini Panda, 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks pdf

Priyadarshini Panda, Abhishek Moitra, Rachel Sterneck, 2021, ArXiv.

Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization

Kaushik Roy, Priyadarshini Panda, Sai Aparna Aketi, 2019, ArXiv.

Explainable Learning: Implicit Generative Modelling during Training for Adversarial Robustness pdf

Kaushik Roy, Priyadarshini Panda, 2018, ArXiv.

Analysis of Liquid Ensembles for Enhancing the Performance and Accuracy of Liquid State Machines

Parami Wijesinghe, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2019, Front. Neurosci..

Neural Networks at the Edge

Kaushik Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, 2019, 2019 IEEE International Conference on Smart Computing (SMARTCOMP).

High-Density and Robust STT-MRAM Array Through Device/Circuit/Architecture Interactions

Xuanyao Fong, Parami Wijesinghe, Kaushik Roy, 2015, IEEE Transactions on Nanotechnology.

Tree-CNN: A Deep Convolutional Neural Network for Lifelong Learning pdf

Kaushik Roy, Priyadarshini Panda, Deboleena Roy, 2018, ArXiv.

Voltage-Driven Domain-Wall Motion based Neuro-Synaptic Devices for Dynamic On-line Learning

Kaushik Roy, Priyadarshini Panda, Amogh Agrawal, 2017 .

A Low Effort Approach to Structured CNN Design Using PCA

Kaushik Roy, Priyadarshini Panda, Isha Garg, 2018, IEEE Access.

Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing

Kaushik Roy, Priyadarshini Panda, Chankyu Lee, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural Networks

Jason M. Allred, Kaushik Roy, Priyadarshini Panda, 2017, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks pdf

Priyadarshini Panda, Abhiroop Bhattacharjee, 2020, ArXiv.

Learning and Design Methodologies for Efficient, Robust Neural Networks

Priyadarshini Panda, 2019 .

Discretization Based Solutions for Secure Machine Learning Against Adversarial Attacks

Kaushik Roy, Indranil Chakraborty, Priyadarshini Panda, 2019, IEEE Access.

Learning Spatio-Temporal Representations Using Spike-Based Backpropagation

Priyadarshini Panda, Deboleena Roy, Kaushik Roy, 2018 .

Energy Efficient Neural Computing: A Study of Cross-Layer Approximations

Anand Raghunathan, Parami Wijesinghe, Kaushik Roy, 2018, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

A SINGLE SHOT PCA-DRIVEN ANALYSIS OF NETWORK STRUCTURE TO REMOVE REDUNDANCY

Priyadarshini Panda, Kaushik Roy, Isha Garg, 2018 .

Energy-Efficient and Improved Image Recognition with Conditional Deep Learning

Kaushik Roy, Priyadarshini Panda, Abhronil Sengupta, 2017, ACM J. Emerg. Technol. Comput. Syst..

Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch pdf

Priyadarshini Panda, Youngeun Kim, 2020, ArXiv.

Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model

Narayan Srinivasa, Priyadarshini Panda, N. Srinivasa, 2017, Front. Neurosci..

Neuromorphic Computing Enabled by Spin-Transfer Torque Devices

Kaushik Roy, Anand Raghunathan, Priyadarshini Panda, 2016, 2016 29th International Conference on VLSI Design and 2016 15th International Conference on Embedded Systems (VLSID).

Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity

Kaushik Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Gabor filter assisted energy efficient fast learning Convolutional Neural Networks

Kaushik Roy, Priyadarshini Panda, Syed Shakib Sarwar, 2017, 2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

Neural Computing With Magnetoelectric Domain-Wall-Based Neurosynaptic Devices

Kaushik Roy, Priyadarshini Panda, Amogh Agrawal, 2021, IEEE Transactions on Magnetics.

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation pdf

Kaushik Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, 2020, ICLR.

Compression-aware Continual Learning using Singular Value Decomposition pdf

Priyadarshini Panda, Varigonda Pavan Teja, P. Panda, 2020, ArXiv.

Relevant-features based Auxiliary Cells for Robust and Energy Efficient Deep Learning

Kaushik Roy, Priyadarshini Panda, Aparna Aketi, 2019 .

Federated Learning With Spiking Neural Networks

Leandros Tassiulas, Priyadarshini Panda, Youngeun Kim, 2021, IEEE Transactions on Signal Processing.

Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks pdf

Priyadarshini Panda, Abhiroop Bhattacharjee, Lakshya Bhatnagar, 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).

2021 Roadmap on Neuromorphic Computing and Engineering pdf

Gouhei Tanaka, Chiara Bartolozzi, Giacomo Indiveri, 2021, ArXiv.

2022 roadmap on neuromorphic computing and engineering

Gouhei Tanaka, Mufti Mahmud, Chiara Bartolozzi, 2021, Neuromorph. Comput. Eng..

Activation Density Driven Efficient Pruning in Training

Priyadarshini Panda, Timothy Foldy-Porto, Yeshwanth Venkatesha, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Neural Architecture Search for Spiking Neural Networks

Priyadarshini Panda, Yuhang Li, Yeshwanth Venkatesha, 2022 .

Beyond classification: directly training spiking neural networks for semantic segmentation pdf

Priyadarshini Panda, Youngeun Kim, Joshua Chough, 2021, Neuromorph. Comput. Eng..

Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing

Priyadarshini Panda, Youngeun Kim, P. Panda, 2021, Neural Networks.

PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks pdf

Priyadarshini Panda, Youngeun Kim, Yeshwanth Venkatesha, 2021, ArXiv.

Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks

Priyadarshini Panda, Abhiroop Bhattacharjee, Abhishek Moitra, 2021, 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Visual explanations from spiking neural networks using inter-spike intervals

Priyadarshini Panda, Youngeun Kim, P. Panda, 2021, Scientific Reports.

PrivateSNN: Privacy-Preserving Spiking Neural Networks

Priyadarshini Panda, Youngeun Kim, Yeshwanth Venkatesha, 2021 .

Implicit adversarial data augmentation and robustness with Noise-based Learning

Kaushik Roy, Priyadarshini Panda, 2021, Neural Networks.

NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars

Priyadarshini Panda, Abhiroop Bhattacharjee, Lakshya Bhatnagar, 2022, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar

Priyadarshini Panda, Youngeun Kim, Hyunsoo Kim, 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks pdf

Priyadarshini Panda, Abhishek Moitra, Rachel Sterneck, 2021, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning pdf

Priyadarshini Panda, Arijit Raychowdhury, Malik Aqeel Anwar, 2021, 2022 International Conference on Robotics and Automation (ICRA).

Domain Adaptation Without Source Data

Sungeun Hong, Priyadarshini Panda, Youngeun Kim, 2020, IEEE Transactions on Artificial Intelligence.