A Multi-Functional In-Memory Inference Processor Using a Standard 6T SRAM Array von Mingu Kang, Gonugondla, Sujan K., Patil, Ameya, Shanbhag, Naresh R.

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A Variation-Tolerant In-Memory Machine Learning Classifier via On-Chip Training von Gonugondla, Sujan K., Kang, Mingu, Shanbhag, Naresh R.

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An Energy-Efficient ECG Processor in 45-nm CMOS Using Statistical Error Compensation von Abdallah, Rami A., Shanbhag, Naresh R.

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Energy-Accuracy Trade-Offs for Resistive In-Memory Computing Architectures von Roy, Saion K., Shanbhag, Naresh R.

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Enhancing the Accuracy of 6T SRAM-Based In-Memory Architecture via Maximum Likelihood Detection von Kim, Hyungyo, Shanbhag, Naresh R.

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Deep in-Memory Architectures for Machine Learning von Kang, Mingu, Gonugondla, Sujan, Shanbhag, Naresh R

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Signal Processing Methods to Enhance the Energy Efficiency of In-Memory Computing Architectures von Sakr, Charbel, Shanbhag, Naresh R.

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Benchmarking In-Memory Computing Architectures von Shanbhag, Naresh R., Roy, Saion K.

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Deep In-Memory Architectures in SRAM: An Analog Approach to Approximate Computing von Kang, Mingu, Gonugondla, Sujan K., Shanbhag, Naresh R.

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A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting von Dbouk, Hassan, Gonugondla, Sujan K., Sakr, Charbel, Shanbhag, Naresh R.

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Binodal, wireless epidermal electronic systems with in-sensor analytics for neonatal intensive care von Chung, Ha Uk, Kim, Bong Hoon, Lee, Jong Yoon, Lee, Jungyup, Xie, Zhaoqian, Ibler, Erin M, Lee, KunHyuck, Banks, Anthony, Jeong, Ji Yoon, Kim, Jongwon, Ogle, Christopher, Grande, Dominic, Yu, Yongjoon, Jang, Hokyung, Assem, Pourya, Ryu, Dennis, Kwak, Jean Won, Namkoong, Myeong, Park, Jun Bin, Lee, Yechan, Kim, Do Hoon, Ryu, Arin, Jeong, Jaeseok, You, Kevin, Ji, Bowen, Liu, Zhuangjian, Huo, Qingze, Feng, Xue, Deng, Yujun, Xu, Yeshou, Jang, Kyung-In, Kim, Jeonghyun, Zhang, Yihui, Ghaffari, Roozbeh, Rand, Casey M, Schau, Molly, Hamvas, Aaron, Weese-Mayer, Debra E, Huang, Yonggang, Lee, Seung Min, Lee, Chi Hwan, Shanbhag, Naresh R, Paller, Amy S, Xu, Shuai, Rogers, John A

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Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications von Gonugondla, Sujan K., Sakr, Charbel, Dbouk, Hassan, Shanbhag, Naresh R.

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Deep In-Memory Architectures for Machine Learning-Accuracy Versus Efficiency Trade-Offs von Kang, Mingu, Kim, Yongjune, Patil, Ameya D., Shanbhag, Naresh R.

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Embedded Algorithmic Noise-Tolerance for Signal Processing and Machine Learning Systems via Data Path Decomposition von Sai Zhang, Shanbhag, Naresh R.

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An In-Memory VLSI Architecture for Convolutional Neural Networks von Kang, Mingu, Lim, Sungmin, Gonugondla, Sujan, Shanbhag, Naresh R.

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Efficient Local Secret Sharing for Distributed Blockchain Systems von Kim, Yongjune, Raman, Ravi Kiran, Kim, Young-Sik, Varshney, Lav R., Shanbhag, Naresh R.

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Error-Resilient Spintronics via the Shannon- Inspired Model of Computation von Patil, Ameya D., Manipatruni, Sasikanth, Nikonov, Dmitri E., Young, Ian A., Shanbhag, Naresh R.

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Slicer Architectures for Analog-to-Information Conversion in Channel Equalizers von Wadhwa, Aseem, Madhow, Upamanyu, Shanbhag, Naresh R.

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Shannon-Inspired Statistical Computing for the Nanoscale Era von Shanbhag, Naresh R., Verma, Naveen, Kim, Yongjune, Patil, Ameya D., Varshney, Lav R.

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Boosted Spin Channel Networks for Energy-Efficient Inference von Patil, Ameya D., Manipatruni, Sasikanth, Nikonov, Dmitri E., Young, Ian A., Shanbhag, Naresh R.

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