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Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers., , , , , , , , , and 6 other author(s). ISCAS, page 3319-3323. IEEE, (2022)Circuit Techniques for Efficient Acceleration of Deep Neural Network Inference with Analog-AI (Invited)., , , , , , , , , and 2 other author(s). ISCAS, page 1-5. IEEE, (2021)Optimization of Analog Accelerators for Deep Neural Networks Inference., , , , , , , , and . ISCAS, page 1-5. IEEE, (2020)Accelerating Deep Neural Networks with Analog Memory Devices., , , , , , , , and . AICAS, page 149-152. IEEE, (2020)Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited)., , , , , , , , , and 13 other author(s). ISCAS, page 1-5. IEEE, (2023)Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices., , , , , , , , , and 1 other author(s). Frontiers Comput. Neurosci., (2021)Phase Change Memory-based Hardware Accelerators for Deep Neural Networks (invited)., , , , , , , , , and 15 other author(s). VLSI Technology and Circuits, page 1-2. IEEE, (2023)Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges., , , , , , , , , and . IRPS, page 1-10. IEEE, (2020)An analog-AI chip for energy-efficient speech recognition and transcription., , , , , , , , , and 14 other author(s). Nat., 620 (7975): 768-775 (2023)