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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)4-Bit Quantization of LSTM-Based Speech Recognition Models., , , , , , , , , and 2 other author(s). Interspeech, page 2586-2590. ISCA, (2021)An analog-AI chip for energy-efficient speech recognition and transcription., , , , , , , , , and 14 other author(s). Nat., 620 (7975): 768-775 (2023)Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges., , , , , , , , , and . IRPS, page 1-10. IEEE, (2020)Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators., , , , , , , , , and 3 other author(s). CoRR, (2023)Sputtering of Metal Oxide Semiconductor n-p Stacks., , , , and . ISOEN, page 1-3. IEEE, (2019)Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization., , , , , , , and . INTERSPEECH, page 2038-2042. ISCA, (2022)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)