| Experimental demonstration and tolerancing of a large-scale neural network (165 000 synapses) using phase-change memory as the synaptic weight element GW Burr, RM Shelby, S Sidler, C Di Nolfo, J Jang, I Boybat, RS Shenoy, ... IEEE Transactions on Electron Devices 62 (11), 3498-3507, 2015 | 945 | 2015 |
| Neuromorphic computing using non-volatile memory GW Burr, RM Shelby, A Sebastian, S Kim, S Kim, S Sidler, K Virwani, ... Advances in Physics: X 2 (1), 89-124, 2017 | 939 | 2017 |
| Equivalent-accuracy accelerated neural-network training using analogue memory S Ambrogio, P Narayanan, H Tsai, RM Shelby, I Boybat, C Di Nolfo, ... Nature 558 (7708), 60-67, 2018 | 835 | 2018 |
| Neuromorphic computing with multi-memristive synapses I Boybat, M Le Gallo, SR Nandakumar, T Moraitis, T Parnell, T Tuma, ... Nature communications 9 (1), 2514, 2018 | 558 | 2018 |
| 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 | 263 | 2020 |
| Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Comparative performance analysis (accuracy, speed, and power) GW Burr, P Narayanan, RM Shelby, S Sidler, I Boybat, C Di Nolfo, ... 2015 IEEE International Electron Devices Meeting (IEDM), 4.4. 1-4.4. 4, 2015 | 176 | 2015 |
| Signal and noise extraction from analog memory elements for neuromorphic computing N Gong, T Idé, S Kim, I Boybat, A Sebastian, V Narayanan, T Ando Nature communications 9 (1), 2102, 2018 | 88 | 2018 |
| A phase-change memory model for neuromorphic computing SR Nandakumar, M Le Gallo, I Boybat, B Rajendran, A Sebastian, ... Journal of Applied Physics 124 (15), 152135, 2018 | 86 | 2018 |
| 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 | 71 | 2020 |
| Mixed-precision architecture based on computational memory for training deep neural networks SR Nandakumar, M Le Gallo, I Boybat, B Rajendran, A Sebastian, ... 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018 | 66 | 2018 |
| Experimental demonstration of supervised learning in spiking neural networks with phase-change memory synapses SR Nandakumar, I Boybat, M Le Gallo, E Eleftheriou, A Sebastian, ... Scientific reports 10 (1), 1-11, 2020 | 44 | 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 | 43 | 2019 |
| Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: Impact of conductance response S Sidler, I Boybat, RM Shelby, P Narayanan, J Jang, A Fumarola, K Moon, ... 2016 46th European Solid-State Device Research Conference (ESSDERC), 440-443, 2016 | 43 | 2016 |
| A hardware-oriented dynamically adaptive disparity estimation algorithm and its real-time hardware A Akin, I Baz, B Atakan, I Boybat, A Schmid, Y Leblebici Proceedings of the 23rd ACM international conference on Great lakes …, 2013 | 26* | 2013 |
| 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 | 22 | 2019 |
| Stochastic weight updates in phase-change memory-based synapses and their influence on artificial neural networks I Boybat, M Le Gallo, T Moraitis, Y Leblebici, A Sebastian, E Eleftheriou 2017 13th Conference on Ph. D. Research in Microelectronics and Electronics …, 2017 | 22 | 2017 |
| Mixed-precision training of deep neural networks using computational memory R Nandakumar S, M Le Gallo, I Boybat, B Rajendran, A Sebastian, ... arXiv e-prints, arXiv: 1712.01192, 2017 | 21 | 2017 |
| Improved deep neural network hardware-accelerators based on non-volatile-memory: The local gains technique I Boybat, C Di Nolfo, S Ambrogio, M Bodini, NCP Farinha, RM Shelby, ... 2017 IEEE International Conference on Rebooting Computing (ICRC), 1-8, 2017 | 19 | 2017 |
| Supervised learning in spiking neural networks with MLC PCM synapses SR Nandakumar, I Boybat, M Le Gallo, A Sebastian, B Rajendran, ... 2017 75th Annual Device Research Conference (DRC), 1-2, 2017 | 19 | 2017 |
| Non-volatile memory as hardware synapse in neuromorphic computing: A first look at reliability issues RM Shelby, GW Burr, I Boybat, C Di Nolfo 2015 IEEE International Reliability Physics Symposium, 6A. 1.1-6A. 1.6, 2015 | 17 | 2015 |
Abu SebastianDistinguished Scientist, IBM Research - ZurichVerified email at zurich.ibm.com
