Efficient FeFET Crossbar Accelerator for Binary Neural Networks. - Taha Soliman; Ricardo Olivo; Tobias Kirchner; Cecilia De la Parra; Maximilian Lederer; Thomas Kämpfe; Andre Guntoro; Norbert Wehn (ASAP, 2020)

Next Generation Arithmetic for Edge Computing. - Andre Guntoro; Cecilia De la Parra; Farhad Merchant; Florent de Dinechin; John L. Gustafson; Martin Langhammer; Rainer Leupers; Sangeeth Nambiar (DATE, 2020)

ProxSim: GPU-based Simulation Framework for Cross-Layer Approximate DNN Optimization. - Cecilia De la Parra; Andre Guntoro; Akash Kumar 001 (DATE, 2020)

Full Approximation of Deep Neural Networks through Efficient Optimization. - Cecilia De la Parra; Andre Guntoro; Akash Kumar 001 (ISCAS, 2020)

Improving approximate neural networks for perception tasks through specialized optimization. - Cecilia De la Parra; Andre Guntoro; Akash Kumar 001 (Future Gener. Comput. Syst., 2020)

Adaptable Approximation Based on Bit Decomposition for Deep Neural Network Accelerators. - Taha Soliman; Cecilia De la Parra; Andre Guntoro; Norbert Wehn (AICAS, 2021)

Efficient Accuracy Recovery in Approximate Neural Networks by Systematic Error Modelling. - Cecilia De la Parra; Andre Guntoro; Akash Kumar 001 (ASP-DAC, 2021)

A Novel DRAM-Based Process-in-Memory Architecture and its Implementation for CNNs. - Chirag Sudarshan; Taha Soliman; Cecilia De la Parra; Christian Weis; Leonardo Ecco; Matthias Jung 001; Norbert Wehn; Andre Guntoro (ASP-DAC, 2021)

Knowledge Distillation and Gradient Estimation for Active Error Compensation in Approximate Neural Networks. - Cecilia De la Parra; Xuyi Wu; Andre Guntoro; Akash Kumar 001 (DATE, 2021)

Exploiting Resiliency for Kernel-Wise CNN Approximation Enabled by Adaptive Hardware Design. - Cecilia De la Parra; Ahmed El-Yamany; Taha Soliman; Akash Kumar 001; Norbert Wehn; Andre Guntoro (ISCAS, 2021)

Efficient Hardware Approximation for Bit-Decomposition Based Deep Neural Network Accelerators. - Taha Soliman; Amro Eldebiky; Cecilia De la Parra; Andre Guntoro; Norbert Wehn (SOCC, 2022)

Increasing Throughput of In-Memory DNN Accelerators by Flexible Layerwise DNN Approximation. - Cecilia De la Parra; Taha Soliman; Andre Guntoro; Akash Kumar 001; Norbert Wehn (IEEE Micro, 2022)

Torwards Variability Immune Scalable FeFET-based Macros for IMC DNN Accelerators. - Nellie Laleni; Taha Soliman; Cecilia De la Parra; Franz Müller 001; Tobias Kirchner; Andre Guntoro; Thomas Kämpfe; Norbert Wehn; T. Jang (ICECS, 2023)

Accelerating Automated Driving and ADAS Using HW/SW Codesign. - Shubham Rai; Cecilia De la Parra; Martin Rapp; Jan Micha Borrmann; Nina Bretz; Stefan Metzlaff; Taha Soliman; Christoph Schorn (SOCC, 2024)

Post-Training Optimization of Cross-layer Approximate Computing for Edge Inference of Deep Learning Applications. - Cecilia De la Parra (2024)

MixA-Q: Revisiting Activation Sparsity for Vision Transformers from a Mixed-Precision Quantization Perspective. - Weitian Wang; Shubham Rai; Cecilia De la Parra; Akash Kumar 001 (CoRR, 2025)