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DrowsyNet: Convolutional neural networks with runtime power-accuracy tunability using inference-stage dropout., , , , and . VLSI-DAT, page 1-4. IEEE, (2018)A 65nm 1Mb nonvolatile computing-in-memory ReRAM macro with sub-16ns multiply-and-accumulate for binary DNN AI edge processors., , , , , , , , , and 7 other author(s). ISSCC, page 494-496. IEEE, (2018)A 1Mb Multibit ReRAM Computing-In-Memory Macro with 14.6ns Parallel MAC Computing Time for CNN Based AI Edge Processors., , , , , , , , , and 12 other author(s). ISSCC, page 388-390. IEEE, (2019)Considerations Of Integrating Computing-In-Memory And Processing-In-Sensor Into Convolutional Neural Network Accelerators For Low-Power Edge Devices., , , , , , , , , and 3 other author(s). VLSI Circuits, page 166-. IEEE, (2019)VST: A virtual stress testing framework for discovering bugs in SSD flash-translation layers., , and . ICCAD, page 283-290. IEEE, (2017)Physically Tightly Coupled, Logically Loosely Coupled, Near-Memory BNN Accelerator (PTLL-BNN)., , , , , , , and . ESSCIRC, page 241-244. IEEE, (2019)5.9 A 0.8V Multimode Vision Sensor for Motion and Saliency Detection with Ping-Pong PWM Pixel., , , , , , , , , and 3 other author(s). ISSCC, page 110-112. IEEE, (2020)A 0.8 V Intelligent Vision Sensor With Tiny Convolutional Neural Network and Programmable Weights Using Mixed-Mode Processing-in-Sensor Technique for Image Classification., , , , , , , and . IEEE J. Solid State Circuits, 58 (11): 3266-3274 (November 2023)Built-in Self-Test and Built-in Self-Repair Strategies Without Golden Signature for Computing in Memory., , , , and . DATE, page 1-6. IEEE, (2023)Parallelization and characterization of GARCH option pricing on GPUs., , and . IISWC, page 1-10. IEEE Computer Society, (2010)