Rapid learning with phase-change memory-based in-memory computing through learning-to-learn by Thomas Ortner, Horst Petschenig, Athanasios Vasilopoulos, Roland Renner, Špela Brglez, Thomas Limbacher, Enrique Piñero, Alejandro Linares-Barranco, Angeliki Pantazi, Robert Legenstein

“…In this work, we pair L2L with in-memory computing NMHW based on phase-change memory devices to build efficient AI models that can rapidly adapt to new tasks. …”
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A Readout Scheme for PCM-Based Analog In-Memory Computing With Drift Compensation Through Reference Conductance Tracking by Alessio Antolini, Andrea Lico, Francesco Zavalloni, Eleonora Franchi Scarselli, Antonio Gnudi, Mattia Luigi Torres, Roberto Canegallo, Marco Pasotti

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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

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Scalability of Phase Change Materials in Nanostructure Template by Wei Zhang, Biyun L. Jackson, Ke Sun, Jae Young Lee, Shyh-Jer Huang, Hsin-Chieh Yu, Sheng-Po Chang, Shoou-Jinn Chang, Ya-Hong Xie

“…Therefore, the phase change memory applications are of great importance in terms of energy saving.…”
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Study of Ge-Sb-Te Superlattice Structure Based on Topological Descriptors by Xiujun Zhang, Muhammad Naeem, Abdul Rauf, Adnan Aslam, Zafar Iqbal, Abudulai Issa

“…Ge-Sb-Te superlattice is a new electronic material that is capable of storing nonvolatile phase-change memories with very low energy consumption. Topological descriptors are numerical values given to molecular structures that may be used to predict specific physical/chemical characteristics. …”
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