| Accurate deep neural network inference using computational phase-change memory V Joshi, M Le Gallo, S Haefeli, I Boybat, SR Nandakumar, C Piveteau, ... Nature communications 11 (1), 2473, 2020 | 403 | 2020 |
| Mixed-precision deep learning based on computational memory SR Nandakumar, M Le Gallo, C Piveteau, V Joshi, G Mariani, I Boybat, ... Frontiers in neuroscience 14, 406, 2020 | 98 | 2020 |
| Error mitigation for universal gates on encoded qubits C Piveteau, D Sutter, S Bravyi, JM Gambetta, K Temme Physical review letters 127 (20), 200505, 2021 | 79 | 2021 |
| Circuit knitting with classical communication C Piveteau, D Sutter IEEE Transactions on Information Theory, 2023 | 63 | 2023 |
| Bulk and nanocrystalline cesium lead-halide perovskites as seen by halide magnetic resonance L Piveteau, M Aebli, N Yazdani, M Millen, L Korosec, F Krieg, BM Benin, ... ACS central science 6 (7), 1138-1149, 2020 | 52 | 2020 |
| Computational memory-based inference and training of deep neural networks A Sebastian, I Boybat, M Dazzi, I Giannopoulos, V Jonnalagadda, V Joshi, ... 2019 Symposium on VLSI Technology, T168-T169, 2019 | 47 | 2019 |
| Quasiprobability decompositions with reduced sampling overhead C Piveteau, D Sutter, S Woerner npj Quantum Information 8 (1), 12, 2022 | 37 | 2022 |
| Deep learning acceleration based on in-memory computing E Eleftheriou, M Le Gallo, SR Nandakumar, C Piveteau, I Boybat, V Joshi, ... IBM Journal of Research and Development 63 (6), 7: 1-7: 16, 2019 | 31 | 2019 |
| Phase-change memory models for deep learning training and inference SR Nandakumar, I Boybat, V Joshi, C Piveteau, M Le Gallo, B Rajendran, ... 2019 26th IEEE International Conference on Electronics, Circuits and Systems …, 2019 | 24 | 2019 |
| : A reference Dirac semimetal QS Wu, C Piveteau, Z Song, OV Yazyev Physical Review B 98 (8), 081115, 2018 | 22 | 2018 |
| Optimal wire cutting with classical communication L Brenner, C Piveteau, D Sutter arXiv preprint arXiv:2302.03366, 2023 | 20 | 2023 |
| Multi-ReRAM synapses for artificial neural network training I Boybat, C Giovinazzo, E Shahrabi, I Krawczuk, I Giannopoulos, ... 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019 | 11 | 2019 |
| Cutting circuits with multiple two-qubit unitaries L Schmitt, C Piveteau, D Sutter arXiv preprint arXiv:2312.11638, 2023 | 10 | 2023 |
| Quantum message-passing algorithm for optimal and efficient decoding C Piveteau, JM Renes Quantum 6, 784, 2022 | 10 | 2022 |
| Circuit knitting with classical communication. 2022 C Piveteau, D Sutter Preprint, 2022 | 9 | 2022 |
| Training of artificial neural networks C Piveteau, A Sebastian, M Le Gallo-Bourdeau, VM Joshi US Patent 11,373,092, 2022 | 8 | 2022 |
| Tensor network decoding beyond 2D C Piveteau, CT Chubb, JM Renes arXiv preprint arXiv:2310.10722, 2023 | 5 | 2023 |
| Advanced methods for quasiprobabilistic quantum error mitigation C Piveteau ETH Zurich, Institute of Theoretical Physics, 2020 | 5 | 2020 |
| Training of artificial neural networks M Le Gallo-Bourdeau, NS Rajalekshmi, C Piveteau, IB Kara, A Sebastian, ... US Patent 11,386,319, 2022 | 4 | 2022 |
| Electronic system for performing a multiplication of a matrix and vector C Piveteau, A Sebastian, M Le Gallo-Bourdeau, R Khaddam-Aljameh US Patent 11,042,715, 2021 | 4 | 2021 |
