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A Fast and Scalable Pipeline for Stain Normalization of Whole-Slide Images in Histopathology., , , , , , , , and . ECCV Workshops (6), volume 11134 of Lecture Notes in Computer Science, page 424-436. Springer, (2018)Design and realization of a fault-tolerant 90nm CMOS cryptographic engine capable of performing under massive defect density., , , , and . ACM Great Lakes Symposium on VLSI, page 204-207. ACM, (2007)Output probability density functions of logic circuits: Modeling and fault-tolerance evaluation., , and . VLSI-SoC, page 328-334. IEEE, (2010)Multilevel-Cell Phase-Change Memory: A Viable Technology., , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 6 (1): 87-100 (2016)Phase-change memory: Feasibility of reliable multilevel-cell storage and retention at elevated temperatures., , , , and . IRPS, page 5. IEEE, (2015)Acceleration of Decision-Tree Ensemble Models on the IBM Telum Processor., , , , , , , , , and 1 other author(s). ISCAS, page 1-5. IEEE, (2023)Fault-Tolerance of Robust Feed-Forward Architecture Using Single-Ended and Differential Deep-Submicron Circuits Under Massive Defect Density., , and . IJCNN, page 2771-2778. IEEE, (2006)Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices., , , , , , , , , and 1 other author(s). Frontiers Comput. Neurosci., (2021)Deep learning acceleration based on in-memory computing., , , , , , , , , and 7 other author(s). IBM J. Res. Dev., 63 (6): 7:1-7:16 (2019)A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference., , , , , , , , , and 19 other author(s). CoRR, (2022)