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ORCIDKaushik Roy 0001
Person information
- affiliation: Purdue University, West Lafayette, IN, USA
Other persons with the same name
- Kaushik Roy — disambiguation page
- Kaushik Roy 0002 — Institute for Information Systems Engineering, Concordia University
- Kaushik Roy 0003 — North Carolina State University, Raleigh, NC, USA
- Kaushik Roy 0004
![[0000-0002-3360-7576]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3360-7576")
— West Bengal State University, Barasat, India - Kaushik Roy 0005 — RV College of Engineering, Bangalore, India
- Kaushik Roy 0006 — University of Windsor, Canada
- Kaushik Roy 0007 — Stanford University, Stanford, CA, USA
- Kaushik Roy 0008 — Sungkyunkwan University, MOPIC, R&B Center, Suwon-si, South Korea (and 1 more)
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2020 – today
- 2021
[j236]Efstathia Soufleri, Kaushik Roy:
Network Compression via Mixed Precision Quantization Using a Multi-Layer Perceptron for the Bit-Width Allocation. IEEE Access 9: 135059-135068 (2021)- [j235]Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy:
Towards understanding the effect of leak in Spiking Neural Networks. Neurocomputing 464: 83-94 (2021) - [j234]Priyadarshini Panda, Kaushik Roy:
Implicit adversarial data augmentation and robustness with Noise-based Learning. Neural Networks 141: 120-132 (2021) - [j233]Shubham Jain, Abhronil Sengupta, Kaushik Roy, Anand Raghunathan:
RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(2): 326-338 (2021) - [j232]Amogh Agrawal, Cheng Wang, Tanvi Sharma, Kaushik Roy:
Magnetoresistive Circuits and Systems: Embedded Non-Volatile Memory to Crossbar Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. 68(6): 2281-2294 (2021) - [j231]Nitin Rathi, Kaushik Roy:
STDP Based Unsupervised Multimodal Learning With Cross-Modal Processing in Spiking Neural Networks. IEEE Trans. Emerg. Top. Comput. Intell. 5(1): 143-153 (2021) - [c452]Sitao Huang, Aayush Ankit, Plínio Silveira, Rodrigo Antunes, Sai Rahul Chalamalasetti, Izzat El Hajj, Dong Eun Kim, Glaucimar Aguiar, Pedro Bruel, Sergey Serebryakov, Cong Xu, Can Li, Paolo Faraboschi, John Paul Strachan, Deming Chen, Kaushik Roy, Wen-Mei W. Hwu, Dejan S. Milojicic:
Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. ASP-DAC 2021: 372-377 - [c451]Wachirawit Ponghiran, Kaushik Roy:
Hybrid Analog-Spiking Long Short-Term Memory for Energy Efficient Computing on Edge Devices. DATE 2021: 581-586 - [c450]Nitin Rathi, Amogh Agrawal, Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy:
Exploring Spike-Based Learning for Neuromorphic Computing: Prospects and Perspectives. DATE 2021: 902-907 - [c449]Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan, Kaushik Roy:
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems. ICDCS 2021: 573-583 - [c448]Gobinda Saha, Isha Garg, Kaushik Roy:
Gradient Projection Memory for Continual Learning. ICLR 2021 - [c447]Sayeed Shafayet Chowdhury, Isha Garg, Kaushik Roy:
Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks. IJCNN 2021: 1-9 - [c446]Tanvi Sharma, Cheng Wang, Amogh Agrawal, Kaushik Roy:
Enabling Robust SOT-MTJ Crossbars for Machine Learning using Sparsity-Aware Device-Circuit Co-design. ISLPED 2021: 1-6 - [i113]Gobinda Saha, Isha Garg, Kaushik Roy:
Gradient Projection Memory for Continual Learning. CoRR abs/2103.09762 (2021) - [i112]Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy:
Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures. CoRR abs/2103.10592 (2021) - [i111]Sayeed Shafayet Chowdhury, Isha Garg, Kaushik Roy:
Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks. CoRR abs/2104.12528 (2021) - [i110]Amogh Agrawal, Mustafa Fayez Ali, Minsuk Koo, Nitin Rathi, Akhilesh Jaiswal, Kaushik Roy:
IMPULSE: A 65nm Digital Compute-in-Memory Macro with Fused Weights and Membrane Potential for Spike-based Sequential Learning Tasks. CoRR abs/2105.08217 (2021) - [i109]Shubham Negi, Indranil Chakraborty, Aayush Ankit, Kaushik Roy:
NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems. CoRR abs/2106.12125 (2021) - [i108]Wachirawit Ponghiran, Kaushik Roy:
Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning. CoRR abs/2109.01905 (2021) - [i107]Gobinda Saha, Kaushik Roy:
Saliency Guided Experience Packing for Replay in Continual Learning. CoRR abs/2109.04954 (2021) - [i106]Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan, Kaushik Roy:
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems. CoRR abs/2109.06440 (2021) - [i105]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) - [i104]Deboleena Roy, Chun Tao, Indranil Chakraborty, Kaushik Roy:
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars. CoRR abs/2109.09060 (2021) - [i103]Bing Han, Cheng Wang, Kaushik Roy:
Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing. CoRR abs/2109.13090 (2021) - 2020
- [j230]Isha Garg, Priyadarshini Panda, Kaushik Roy:
A Low Effort Approach to Structured CNN Design Using PCA. IEEE Access 8: 1347-1360 (2020) - [j229]Syed Shakib Sarwar, Aayush Ankit, Kaushik Roy:
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing. IEEE Access 8: 4615-4628 (2020) - [j228]Sai Aparna Aketi, Sourjya Roy, Anand Raghunathan, Kaushik Roy:
Gradual Channel Pruning While Training Using Feature Relevance Scores for Convolutional Neural Networks. IEEE Access 8: 171924-171932 (2020) - [j227]Amogh Agrawal, Adarsh Kosta, Sangamesh Kodge, Dong Eun Kim, Kaushik Roy:
CASH-RAM: Enabling In-Memory Computations for Edge Inference Using Charge Accumulation and Sharing in Standard 8T-SRAM Arrays. IEEE J. Emerg. Sel. Topics Circuits Syst. 10(3): 295-305 (2020) - [j226]Amogh Agrawal, Adarsh Kosta, Sangamesh Kodge, Dong Eun Kim, Kaushik Roy:
Erratum to "CASH-RAM: Enabling In-Memory Computations for Edge Inference Using Charge Accumulation and Sharing in Standard 8T-SRAM Arrays". IEEE J. Emerg. Sel. Topics Circuits Syst. 10(4): 588 (2020) - [j225]Aayush Ankit, Indranil Chakraborty, Amogh Agrawal, Mustafa Fayez Ali, Kaushik Roy:
Circuits and Architectures for In-Memory Computing-Based Machine Learning Accelerators. IEEE Micro 40(6): 8-22 (2020) - [j224]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning. Neural Networks 121: 148-160 (2020) - [j223]Indranil Chakraborty, Mustafa Fayez Ali, Aayush Ankit, Shubham Jain, Sourjya Roy, Shrihari Sridharan, Amogh Agrawal, Anand Raghunathan, Kaushik Roy:
Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges. Proc. IEEE 108(12): 2276-2310 (2020) - [j222]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei Hwu, Kaushik Roy:
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM. IEEE Trans. Computers 69(8): 1128-1142 (2020) - [j221]Aayush Ankit, Timur Ibrayev, Abhronil Sengupta, Kaushik Roy:
TraNNsformer: Clustered Pruning on Crossbar-Based Architectures for Energy-Efficient Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2361-2374 (2020) - [j220]Swagath Venkataramani, Vivek Joy Kozhikkottu, Amit Sabne, Kaushik Roy, Anand Raghunathan:
Logic Synthesis of Approximate Circuits. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(10): 2503-2515 (2020) - [j219]Mustafa Fayez Ali, Akhilesh Jaiswal, Kaushik Roy:
In-Memory Low-Cost Bit-Serial Addition Using Commodity DRAM Technology. IEEE Trans. Circuits Syst. I Regul. Pap. 67-I(1): 155-165 (2020) - [j218]Mustafa Fayez Ali, Robert Andrawis, Kaushik Roy:
Dynamic Read Current Sensing With Amplified Bit-Line Voltage for STT-MRAMs. IEEE Trans. Circuits Syst. II Express Briefs 67-II(3): 551-555 (2020) - [j217]Mustafa Fayez Ali, Akhilesh Jaiswal, Sangamesh Kodge, Amogh Agrawal, Indranil Chakraborty, Kaushik Roy:
IMAC: In-Memory Multi-Bit Multiplication and ACcumulation in 6T SRAM Array. IEEE Trans. Circuits Syst. I Regul. Pap. 67-I(8): 2521-2531 (2020) - [j216]Minsuk Koo, Gopalakrishnan Srinivasan, Yong Shim, Kaushik Roy:
sBSNN: Stochastic-Bits Enabled Binary Spiking Neural Network With On-Chip Learning for Energy Efficient Neuromorphic Computing at the Edge. IEEE Trans. Circuits Syst. I Regul. Pap. 67-I(8): 2546-2555 (2020) - [j215]Akhilesh Jaiswal, Robert Andrawis, Amogh Agrawal, Kaushik Roy:
Functional Read Enabling In-Memory Computations in 1Transistor - 1Resistor Memory Arrays. IEEE Trans. Circuits Syst. 67-II(12): 3347-3351 (2020) - [j214]Akhilesh Jaiswal, Amogh Agrawal, Mustafa Fayez Ali, Saima Sharmin, Kaushik Roy:
i-SRAM: Interleaved Wordlines for Vector Boolean Operations Using SRAMs. IEEE Trans. Circuits Syst. 67-I(12): 4651-4659 (2020) - [j213]Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Utkarsh Saxena, Saima Sharmin, Minsuk Koo, Yong Shim, Gopalakrishnan Srinivasan, Chamika M. Liyanagedera, Abhronil Sengupta, Kaushik Roy:
Revisiting Stochastic Computing in the Era of Nanoscale Nonvolatile Technologies. IEEE Trans. Very Large Scale Integr. Syst. 28(12): 2481-2494 (2020) - [c445]Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy:
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network. CVPR 2020: 13555-13564 - [c444]Kaushik Roy, Indranil Chakraborty, Mustafa Fayez Ali, Aayush Ankit, Amogh Agrawal:
In-Memory Computing in Emerging Memory Technologies for Machine Learning: An Overview. DAC 2020: 1-6 - [c443]Indranil Chakraborty, Mustafa Fayez Ali, Dong Eun Kim, Aayush Ankit, Kaushik Roy:
GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks. DAC 2020: 1-6 - [c442]Chankyu Lee, Adarsh Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy:
Spike-FlowNet: Event-Based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks. ECCV (29) 2020: 366-382 - [c441]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. ECCV (29) 2020: 399-414 - [c440]Gopalakrishnan Srinivasan, Chankyu Lee, Abhronil Sengupta, Priyadarshini Panda, Syed Shakib Sarwar, Kaushik Roy:
Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing. ICASSP 2020: 8549-8553 - [c439]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. ICLR 2020 - [c438]Krishna Reddy Kesari, Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy:
Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity. IJCNN 2020: 1-8 - [c437]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. IJCNN 2020: 1-9 - [c436]Mustafa Fayez Ali, Amogh Agrawal, Kaushik Roy:
RAMANN: in-SRAM differentiable memory computations for memory-augmented neural networks. ISLPED 2020: 61-66 - [c435]Sourav Sanyal, Aayush Ankit, Craig M. Vineyard, Kaushik Roy:
Energy-Efficient Target Recognition using ReRAM Crossbars for Enabling On-Device Intelligence. SiPS 2020: 1-6 - [c434]Priyadarshini Panda, Kaushik Roy:
Invited Talk: Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems. VLSI Design 2020: 1-18 - [i102]Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy:
Structured Compression and Sharing of Representational Space for Continual Learning. CoRR abs/2001.08650 (2020) - [i101]Sai Aparna Aketi, Sourjya Roy, Anand Raghunathan, Kaushik Roy:
Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks. CoRR abs/2002.09958 (2020) - [i100]Sai Aparna Aketi, Priyadarshini Panda, Kaushik Roy:
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors. CoRR abs/2002.11052 (2020) - [i99]Minsuk Koo, Gopalakrishnan Srinivasan, Yong Shim, Kaushik Roy:
sBSNN: Stochastic-Bits Enabled Binary Spiking Neural Network with On-Chip Learning for Energy Efficient Neuromorphic Computing at the Edge. CoRR abs/2002.11163 (2020) - [i98]Jason M. Allred, Steven J. Spencer, Gopalakrishnan Srinivasan, Kaushik Roy:
Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation. CoRR abs/2003.01250 (2020) - [i97]Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy:
RMP-SNNs: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Networks. CoRR abs/2003.01811 (2020) - [i96]Chankyu Lee, Adarsh Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy:
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks. CoRR abs/2003.06696 (2020) - [i95]Indranil Chakraborty, Mustafa Fayez Ali, Dong Eun Kim, Aayush Ankit, Kaushik Roy:
GENIEx: A Generalized Approach to Emulating Non-Ideality in Memristive Xbars using Neural Networks. CoRR abs/2003.06902 (2020) - [i94]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) - [i93]Mustafa Fayez Ali, Akhilesh Jaiswal, Sangamesh Kodge, Amogh Agrawal, Indranil Chakraborty, Kaushik Roy:
IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array. CoRR abs/2003.12558 (2020) - [i92]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) - [i91]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. CoRR abs/2005.04171 (2020) - [i90]Yinghan Long, Indranil Chakraborty, Kaushik Roy:
Conditionally Deep Hybrid Neural Networks Across Edge and Cloud. CoRR abs/2005.10851 (2020) - [i89]Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy:
Towards Understanding the Effect of Leak in Spiking Neural Networks. CoRR abs/2006.08761 (2020) - [i88]Deepak Ravikumar, Sangamesh Kodge, Isha Garg, Kaushik Roy:
TREND: Transferability based Robust ENsemble Design. CoRR abs/2008.01524 (2020) - [i87]Nitin Rathi, Kaushik Roy:
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks. CoRR abs/2008.03658 (2020) - [i86]Deboleena Roy, Indranil Chakraborty, Timur Ibrayev, Kaushik Roy:
Robustness Hidden in Plain Sight: Can Analog Computing Defend Against Adversarial Attacks? CoRR abs/2008.12016 (2020) - [i85]Isha Garg, Sayeed Shafayet Chowdhury, Kaushik Roy:
DCT-SNN: Using DCT to Distribute Spatial Information over Time for Learning Low-Latency Spiking Neural Networks. CoRR abs/2010.01795 (2020) - [i84]Deepak Ravikumar, Sangamesh Kodge, Isha Garg, Kaushik Roy:
Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection. CoRR abs/2012.08398 (2020)
2010 – 2019
- 2019
- [j212]Priyadarshini Panda, Indranil Chakraborty, Kaushik Roy:
Discretization Based Solutions for Secure Machine Learning Against Adversarial Attacks. IEEE Access 7: 70157-70168 (2019) - [j211]Yinghan Long, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Structured Learning for Action Recognition in Videos. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(3): 475-484 (2019) - [j210]Shubham Jain, Aayush Ankit, Indranil Chakraborty, Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch, Kaushik Roy, Anand Raghunathan:
Neural network accelerator design with resistive crossbars: Opportunities and challenges. IBM J. Res. Dev. 63(6): 10:1-10:13 (2019) - [j209]Chankyu Lee, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity. IEEE Trans. Cogn. Dev. Syst. 11(3): 384-394 (2019) - [j208]Amogh Agrawal, Aayush Ankit, Kaushik Roy:
SPARE: Spiking Neural Network Acceleration Using ROM-Embedded RAMs as In-Memory-Computation Primitives. IEEE Trans. Computers 68(8): 1190-1200 (2019) - [j207]Nitin Rathi, Priyadarshini Panda, Kaushik Roy:
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) - [j206]Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy, Bing Han, Gopalakrishnan Srinivasan, Aayush Ankit, Kaushik Roy:
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(8): 3064-3076 (2019) - [j205]Baibhab Chatterjee, Priyadarshini Panda, Shovan Maity, Ayan Biswas, Kaushik Roy, Shreyas Sen:
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) - [j204]Aayush Ankit, Minsuk Koo, Shreyas Sen, Kaushik Roy:
Powerline Communication for Enhanced Connectivity in Neuromorphic Systems. IEEE Trans. Very Large Scale Integr. Syst. 27(8): 1897-1906 (2019) - [j203]Akhilesh Jaiswal, Indranil Chakraborty, Amogh Agrawal, Kaushik Roy:
8T SRAM Cell as a Multibit Dot-Product Engine for Beyond Von Neumann Computing. IEEE Trans. Very Large Scale Integr. Syst. 27(11): 2556-2567 (2019) - [c433]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-mei W. Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic:
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. ASPLOS 2019: 715-731 - [c432]Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok, Kaushik Roy:
Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. IEEE BigData 2019: 4472-4478 - [c431]Akhilesh Jaiswal, Amogh Agrawal, Indranil Chakraborty, Mustafa Fayez Ali, Kaushik Roy:
Digital and Analog-Mixed-Signal In-Memory Processing in CMOS SRAM. ACM Great Lakes Symposium on VLSI 2019: 371 - [c430]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. ICCAD 2019: 1-8 - [c429]Deboleena Roy, Indranil Chakraborty, Kaushik Roy:
Scaling Deep Spiking Neural Networks with Binary Stochastic Activations. ICCC 2019: 50-58 - [c428]Akhilesh Jaiswal, Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Kaushik Roy:
On Robustness of Spin-Orbit-Torque Based Stochastic Sigmoid Neurons for Spiking Neural Networks. IJCNN 2019: 1-6 - [c427]Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy:
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis. IJCNN 2019: 1-8 - [c426]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 - [c425]Deboleena Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, Richard Tomsett, Nirmit Desai, Raghu K. Ganti, Kaushik Roy:
Neural Networks at the Edge. SMARTCOMP 2019: 45-50 - [p3]Ashish Ranjan, Swagath Venkataramani, Shubham Jain, Younghoon Kim, Shankar Ganesh Ramasubramanian, Arnab Raha, Kaushik Roy, Anand Raghunathan:
Automatic Synthesis Techniques for Approximate Circuits. Approximate Circuits 2019: 123-140 - [i83]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-Mei Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic:
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. CoRR abs/1901.10351 (2019) - [i82]Indranil Chakraborty, Deboleena Roy, Aayush Ankit, Kaushik Roy:
Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge. CoRR abs/1902.00460 (2019) - [i81]Priyadarshini Panda, Indranil Chakraborty, Kaushik Roy:
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks. CoRR abs/1902.03151 (2019) - [i80]Jason M. Allred, Kaushik Roy:
Stimulating STDP to Exploit Locality for Lifelong Learning without Catastrophic Forgetting. CoRR abs/1902.03187 (2019) - [i79]Gopalakrishnan Srinivasan, Kaushik Roy:
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing. CoRR abs/1902.04161 (2019) - [i78]Chankyu Lee, Syed Shakib Sarwar, Kaushik Roy:
Enabling Spike-based Backpropagation in State-of-the-art Deep Neural Network Architectures. CoRR abs/1903.06379 (2019) - [i77]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) - [i76]Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy:
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis. CoRR abs/1905.03219 (2019) - [i75]Indranil Chakraborty, Deboleena Roy, Isha Garg, Aayush Ankit, Kaushik Roy:
PCA-driven Hybrid network design for enabling Intelligence at the Edge. CoRR abs/1906.01493 (2019) - [i74]Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy:
Reinforcement Learning with Low-Complexity Liquid State Machines. CoRR abs/1906.01695 (2019) - [i73]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. CoRR abs/1906.08167 (2019) - [i72]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation. CoRR abs/1906.08861 (2019) - [i71]Amogh Agrawal, Chankyu Lee, Kaushik Roy:
X-CHANGR: Changing Memristive Crossbar Mapping for Mitigating Line-Resistance Induced Accuracy Degradation in Deep Neural Networks. CoRR abs/1907.00285 (2019) - [i70]Priyadarshini Panda, Sai Aparna Aketi, Kaushik Roy:
Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization. CoRR abs/1910.13931 (2019) - [i69]Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei W. Hwu, Kaushik Roy:
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM. CoRR abs/1912.11516 (2019) - 2018
- [j202]Priyadarshini Panda, Jason M. Allred, Shriram Ramanathan, Kaushik Roy:
ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural Networks. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 51-64 (2018) - [j201]Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Bing Han, Parami Wijesinghe, Akhilesh Jaiswal, Priyadarshini Panda, Anand Raghunathan, Kaushik Roy:
Energy Efficient Neural Computing: A Study of Cross-Layer Approximations. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 796-809 (2018) - [j200]Syed Shakib Sarwar, Swagath Venkataramani, Aayush Ankit, Anand Raghunathan, Kaushik Roy:
Energy-Efficient Neural Computing with Approximate Multipliers. ACM J. Emerg. Technol. Comput. Syst. 14(2): 16:1-16:23 (2018) - [j199]Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
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) - [j198]Devyani Patra, Ahmed Kamal Reza, Mohammad Khaled Hassan, Mehdi Katoozi, Ethan H. Cannon, Kaushik Roy, Yu Cao:
Adaptive accelerated aging for 28 nm HKMG technology. Microelectron. Reliab. 80: 149-154 (2018) - [j197]Zoha Pajouhi, Kaushik Roy:
Image Edge Detection Based on Swarm Intelligence Using Memristive Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(9): 1774-1787 (2018) - [j196]Amogh Agrawal, Akhilesh Jaiswal, Chankyu Lee, Kaushik Roy:
X-SRAM: Enabling In-Memory Boolean Computations in CMOS Static Random Access Memories. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(12): 4219-4232 (2018) - [j195]Indranil Chakraborty, Deboleena Roy, Kaushik Roy:
Technology Aware Training in Memristive Neuromorphic Systems for Nonideal Synaptic Crossbars. IEEE Trans. Emerg. Top. Comput. Intell. 2(5): 335-344 (2018) - [j194]Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
An All-Memristor Deep Spiking Neural Computing System: A Step Toward Realizing the Low-Power Stochastic Brain. IEEE Trans. Emerg. Top. Comput. Intell. 2(5): 345-358 (2018) - [j193]Bing Han, Aayush Ankit, Abhronil Sengupta, Kaushik Roy:
Cross-Layer Design Exploration for Energy-Quality Tradeoffs in Spiking and Non-Spiking Deep Artificial Neural Networks. IEEE Trans. Multi Scale Comput. Syst. 4(4): 613-623 (2018) - [j192]Bing Han, Kaushik Roy:
DeltaFrame-BP: An Algorithm Using Frame Difference for Deep Convolutional Neural Networks Training and Inference on Video Data. IEEE Trans. Multi Scale Comput. Syst. 4(4): 624-63