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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 — 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
![[0000-0003-2727-6704]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-2727-6704")
— Sungkyunkwan University, MOPIC, R&B Center, Suwon-si, South Korea (and 1 more)
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2020 – today
- 2023
[c484]Gobinda Saha, Kaushik Roy:
Saliency Guided Experience Packing for Replay in Continual Learning. WACV 2023: 5262-5272- [i132]Giovanni Finocchio, Supriyo Bandyopadhyay, Peng Lin, Gang Pan, J. Joshua Yang, Riccardo Tomasello, Christos Panagopoulos, Mario Carpentieri, Vito Puliafito, Johan Åkerman, Hiroki Takesue, Amit Ranjan Trivedi, Saibal Mukhopadhyay, Kaushik Roy, Vinod K. Sangwan, Mark C. Hersam, Anna Giordano, Huynsoo Yang, Julie Grollier, Kerem Camsari, Peter L. McMahon, Supriyo Datta, Jean Anne C. Incorvia, Joseph S. Friedman, Sorin Cotofana, Florin Ciubotaru, Andrii Chumak, Azad J. Naeemi, Brajesh Kumar Kaushik, Yao Zhu, Kang Wang, Belita Koiller, Gabriel Aguilar, Guilherme Temporão, Kremena Makasheva, Aida Tordi-Sanial, Jennifer Hasler, William Levy, Vwani Roychowdhury, Samiran Ganguly, Avik W. Ghosh, Davi Rodriquez, Satoshi Sunada, Karin Evershor-Sitte, Amit Lal, Shubham Jadhav, Massimiliano Di Ventra, Yuriy V. Pershin, Kosuke Tatsumura, Hayato Goto:
Roadmap for Unconventional Computing with Nanotechnology. CoRR abs/2301.06727 (2023) - [i131]Gobinda Saha, Kaushik Roy:
Continual Learning with Scaled Gradient Projection. CoRR abs/2302.01386 (2023) - [i130]Shrihari Sridharan, Jacob R. Stevens, Kaushik Roy, Anand Raghunathan:
X-Former: In-Memory Acceleration of Transformers. CoRR abs/2303.07470 (2023) - 2022
- [j254]Sandip Mondal, Zhen Zhang, A. N. M. Nafiul Islam, Robert Andrawis, Sampath Gamage, Neda Alsadat Aghamiri, Qi Wang, Hua Zhou, Fanny Rodolakis, Richard Tran, Jasleen Kaur, Chi Chen, Shyue Ping Ong, Abhronil Sengupta, Yohannes Abate, Kaushik Roy, Shriram Ramanathan:
All-Electric Nonassociative Learning in Nickel Oxide. Adv. Intell. Syst. 4(10) (2022) - [j253]Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy:
Low precision decentralized distributed training over IID and non-IID data. Neural Networks 155: 451-460 (2022) - [j252]Sourav Sanyal, Kaushik Roy:
Neuro-Ising: Accelerating Large-Scale Traveling Salesman Problems via Graph Neural Network Guided Localized Ising Solvers. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(12): 5408-5420 (2022) - [j251]Chun Tao, Deboleena Roy, Indranil Chakraborty, Kaushik Roy:
On Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars. IEEE Trans. Very Large Scale Integr. Syst. 30(10): 1448-1460 (2022) - [j250]Mustafa Fayez Ali, Sourjya Roy, Utkarsh Saxena, Tanvi Sharma, Anand Raghunathan, Kaushik Roy:
Compute-in-Memory Technologies and Architectures for Deep Learning Workloads. IEEE Trans. Very Large Scale Integr. Syst. 30(11): 1615-1630 (2022) - [c483]Bing Han, Cheng Wang, Kaushik Roy:
Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing. AAAI 2022: 6838-6846 - [c482]Wachirawit Ponghiran, Kaushik Roy:
Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning. AAAI 2022: 8001-8008 - [c481]Sarada Krithivasan, Sanchari Sen, Nitin Rathi, Kaushik Roy, Anand Raghunathan:
Efficiency attacks on spiking neural networks. DAC 2022: 373-378 - [c480]Shubham Negi, Indranil Chakraborty, Aayush Ankit, Kaushik Roy:
NAX: neural architecture and memristive xbar based accelerator co-design. DAC 2022: 451-456 - [c479]Gobinda Saha, Cheng Wang, Anand Raghunathan, Kaushik Roy:
A cross-layer approach to cognitive computing: invited. DAC 2022: 1327-1330 - [c478]Adarsh Kosta, Efstathia Soufleri, Indranil Chakraborty, Amogh Agrawal, Aayush Ankit, Kaushik Roy:
HyperX: A Hybrid RRAM-SRAM partitioned system for error recovery in memristive Xbars. DATE 2022: 88-91 - [c477]Utkarsh Saxena, Indranil Chakraborty, Kaushik Roy:
Towards ADC-Less Compute-In-Memory Accelerators for Energy Efficient Deep Learning. DATE 2022: 624-627 - [c476]Sayeed Shafayet Chowdhury, Nitin Rathi, Kaushik Roy:
Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning. ECCV (11) 2022: 709-726 - [c475]Kaushik Roy:
In-Memory Computing based Machine Learning Accelerators: Opportunities and Challenges. ACM Great Lakes Symposium on VLSI 2022: 203-204 - [c474]Kang He, Indranil Chakraborty, Cheng Wang, Kaushik Roy:
Design Space and Memory Technology Co-Exploration for In-Memory Computing Based Machine Learning Accelerators. ICCAD 2022: 91:1-91:9 - [c473]Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy:
Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures. ICRA 2022: 6504-6510 - [c472]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 - [c471]Deepika Sharma, Aayush Ankit, Kaushik Roy:
Identifying Efficient Dataflows for Spiking Neural Networks. ISLPED 2022: 2:1-2:6 - [p4]Sourav Sanyal, Shubham Negi, Anand Raghunathan, Kaushik Roy:
Approximate Computing for Machine Learning Workloads: A Circuits and Systems Perspective. Approximate Computing 2022: 365-395 - [i129]Isha Garg, Manish Nagaraj, Kaushik Roy:
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data. CoRR abs/2201.08494 (2022) - [i128]Md. Mazharul Islam, Shamiul Alam, Md. Shafayat Hossain, Kaushik Roy, Ahmedullah Aziz:
Cryogenic Neuromorphic Hardware. CoRR abs/2204.07503 (2022) - [i127]Deepak Ravikumar, Kaushik Roy:
Norm-Scaling for Out-of-Distribution Detection. CoRR abs/2205.03493 (2022) - [i126]Wilfried Haensch, Anand Raghunathan, Kaushik Roy, Bhaswar Chakrabarti, Charudatta M. Phatak, Cheng Wang, Supratik Guha:
A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks. CoRR abs/2206.08735 (2022) - [i125]Sourav Sanyal, Kaushik Roy:
RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network. CoRR abs/2209.09025 (2022) - [i124]Adarsh Kumar Kosta, Kaushik Roy:
Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics. CoRR abs/2209.11741 (2022) - [i123]Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy:
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions. CoRR abs/2209.14390 (2022) - [i122]Manish Nagaraj, Chamika Mihiranga Liyanagedera, Kaushik Roy:
DOTIE - Detecting Objects through Temporal Isolation of Events using a Spiking Architecture. CoRR abs/2210.00975 (2022) - [i121]Wachirawit Ponghiran, Chamika Mihiranga Liyanagedera, Kaushik Roy:
Event-based Temporally Dense Optical Flow Estimation with Sequential Neural Networks. CoRR abs/2210.01244 (2022) - [i120]Marco Paul E. Apolinario, Adarsh Kumar Kosta, Utkarsh Saxena, Kaushik Roy:
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks. CoRR abs/2211.02167 (2022) - [i119]Shristi Das Biswas, Adarsh Kosta, Chamika M. Liyanagedera, Marco Paul E. Apolinario, Kaushik Roy:
HALSIE - Hybrid Approach to Learning Segmentation by Simultaneously Exploiting Image and Event Modalities. CoRR abs/2211.10754 (2022) - 2021
- [j249]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) - [j248]Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy:
SPACE: Structured Compression and Sharing of Representational Space for Continual Learning. IEEE Access 9: 150480-150494 (2021) - [j247]Amogh Agrawal, Deboleena Roy, Utkarsh Saxena, Kaushik Roy:
Embracing Stochasticity to Enable Neuromorphic Computing at the Edge. IEEE Des. Test 38(6): 28-35 (2021) - [j246]Aditi Anand, Sanchari Sen, Kaushik Roy:
Quantifying the Brain Predictivity of Artificial Neural Networks With Nonlinear Response Mapping. Frontiers Comput. Neurosci. 15: 609721 (2021) - [j245]Lei Deng, Huajin Tang, Kaushik Roy:
Editorial: Understanding and Bridging the Gap Between Neuromorphic Computing and Machine Learning. Frontiers Comput. Neurosci. 15: 665662 (2021) - [j244]Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy:
Towards understanding the effect of leak in Spiking Neural Networks. Neurocomputing 464: 83-94 (2021) - [j243]Priyadarshini Panda, Kaushik Roy:
Implicit adversarial data augmentation and robustness with Noise-based Learning. Neural Networks 141: 120-132 (2021) - [j242]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) - [j241]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) - [j240]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) - [c470]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 - [c469]Deboleena Roy, Indranil Chakraborty, Timur Ibrayev, Kaushik Roy:
On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks. DAC 2021: 565-570 - [c468]Wachirawit Ponghiran, Kaushik Roy:
Hybrid Analog-Spiking Long Short-Term Memory for Energy Efficient Computing on Edge Devices. DATE 2021: 581-586 - [c467]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 - [c466]Hussam Amrouch, Jian-Jia Chen, Kaushik Roy, Yuan Xie, Indranil Chakraborty, Wenqin Huangfu, Ling Liang, Fengbin Tu, Cheng Wang, Mikail Yayla:
Brain-Inspired Computing: Adventure from Beyond CMOS Technologies to Beyond von Neumann Architectures ICCAD Special Session Paper. ICCAD 2021: 1-9 - [c465]Isha Garg, Sayeed Shafayet Chowdhury, Kaushik Roy:
DCT-SNN: Using DCT to Distribute Spatial Information over Time for Low-Latency Spiking Neural Networks. ICCV 2021: 4651-4660 - [c464]Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan, Kaushik Roy:
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems. ICDCS 2021: 573-583 - [c463]Gobinda Saha, Isha Garg, Kaushik Roy:
Gradient Projection Memory for Continual Learning. ICLR 2021 - [c462]Maryam Parsa, Catherine D. Schuman, Nitin Rathi, Amirkoushyar Ziabari, Derek C. Rose, J. Parker Mitchell, J. Travis Johnston, Bill Kay, Steven R. Young, Kaushik Roy:
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. ICONS 2021: 14:1-14:8 - [c461]Sayeed Shafayet Chowdhury, Isha Garg, Kaushik Roy:
Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks. IJCNN 2021: 1-9 - [c460]Kenneth Chaney, Artemis Panagopoulou, Chankyu Lee, Kaushik Roy, Kostas Daniilidis:
Self-Supervised Optical Flow with Spiking Neural Networks and Event Based Cameras. IROS 2021: 5892-5899 - [c459]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 - [i118]Gobinda Saha, Isha Garg, Kaushik Roy:
Gradient Projection Memory for Continual Learning. CoRR abs/2103.09762 (2021) - [i117]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) - [i116]Sayeed Shafayet Chowdhury, Isha Garg, Kaushik Roy:
Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks. CoRR abs/2104.12528 (2021) - [i115]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) - [i114]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) - [i113]Wachirawit Ponghiran, Kaushik Roy:
Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning. CoRR abs/2109.01905 (2021) - [i112]Gobinda Saha, Kaushik Roy:
Saliency Guided Experience Packing for Replay in Continual Learning. CoRR abs/2109.04954 (2021) - [i111]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) - [i110]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) - [i109]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) - [i108]Bing Han, Cheng Wang, Kaushik Roy:
Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing. CoRR abs/2109.13090 (2021) - [i107]Sayeed Shafayet Chowdhury, Nitin Rathi, Kaushik Roy:
One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency. CoRR abs/2110.05929 (2021) - [i106]Sangamesh Kodge, Kaushik Roy:
BERMo: What can BERT learn from ELMo? CoRR abs/2110.15802 (2021) - [i105]Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy:
Low Precision Decentralized Distributed Training with Heterogeneous Data. CoRR abs/2111.09389 (2021) - [i104]Jason M. Allred, Kaushik Roy:
L4-Norm Weight Adjustments for Converted Spiking Neural Networks. CoRR abs/2111.09446 (2021) - [i103]Amitangshu Mukherjee, Isha Garg, Kaushik Roy:
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift. CoRR abs/2112.10844 (2021) - 2020
- [j239]Isha Garg, Priyadarshini Panda, Kaushik Roy:
A Low Effort Approach to Structured CNN Design Using PCA. IEEE Access 8: 1347-1360 (2020) - [j238]Syed Shakib Sarwar, Aayush Ankit, Kaushik Roy:
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing. IEEE Access 8: 4615-4628 (2020) - [j237]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) - [j236]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) - [j235]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) - [j234]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) - [j233]Indranil Chakraborty, Deboleena Roy, Isha Garg, Aayush Ankit, Kaushik Roy:
Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence. Nat. Mach. Intell. 2(1): 43-55 (2020) - [j232]Deboleena Roy, Priyadarshini Panda, Kaushik Roy:
Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning. Neural Networks 121: 148-160 (2020) - [j231]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) - [j230]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) - [j229]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) - [j228]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) - [j227]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) - [j226]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) - [j225]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) - [j224]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) - [j223]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) - [j222]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) - [j221]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) - [c458]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 - [c457]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 - [c456]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 - [c455]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 - [c454]Bing Han, Kaushik Roy:
Deep Spiking Neural Network: Energy Efficiency Through Time Based Coding. ECCV (10) 2020: 388-404 - [c453]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 - [c452]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 - [c451]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. ICLR 2020 - [c450]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 - [c449]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 - [c448]Mustafa Fayez Ali, Amogh Agrawal, Kaushik Roy:
RAMANN: in-SRAM differentiable memory computations for memory-augmented neural networks. ISLPED 2020: 61-66 - [c447]Ahmedullah Aziz, Kaushik Roy:
Insulator-Metal Transition Material Based Artificial Neurons: A Design Perspective. ISQED 2020: 444-451 - [c446]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 - [c445]Priyadarshini Panda, Kaushik Roy:
Invited Talk: Re-Engineering Computing with Neuro-Inspired Learning: Devices, Circuits, and Systems. VLSID 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)