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Torwards Variability Immune Scalable FeFET-based Macros for IMC DNN Accelerators., , , , , , , , and . ICECS, page 1-4. IEEE, (2023)Efficient Hardware Approximation for Bit-Decomposition Based Deep Neural Network Accelerators., , , , and . SOCC, page 1-6. IEEE, (2022)Post-Training Optimization of Cross-layer Approximate Computing for Edge Inference of Deep Learning Applications.. Dresden University of Technology, Germany, (2024)Increasing Throughput of In-Memory DNN Accelerators by Flexible Layerwise DNN Approximation., , , , and . IEEE Micro, 42 (6): 17-24 (2022)A Novel DRAM-Based Process-in-Memory Architecture and its Implementation for CNNs., , , , , , , and . ASP-DAC, page 35-42. ACM, (2021)Efficient Accuracy Recovery in Approximate Neural Networks by Systematic Error Modelling., , and . ASP-DAC, page 365-371. ACM, (2021)Adaptable Approximation Based on Bit Decomposition for Deep Neural Network Accelerators., , , and . AICAS, page 1-4. IEEE, (2021)Full Approximation of Deep Neural Networks through Efficient Optimization., , and . ISCAS, page 1-5. IEEE, (2020)ProxSim: GPU-based Simulation Framework for Cross-Layer Approximate DNN Optimization., , and . DATE, page 1193-1198. IEEE, (2020)Next Generation Arithmetic for Edge Computing., , , , , , , and . DATE, page 1357-1365. IEEE, (2020)