| Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures J Launay, I Poli, F Boniface, F Krzakala Advances in Neural Information Processing Systems 33, 2020 | 78 | 2020 |
| RITA: a Study on Scaling Up Generative Protein Sequence Models D Hesslow, N Zanichelli, P Notin, I Poli, D Marks arXiv preprint arXiv:2205.05789, 2022 | 62 | 2022 |
| NEWMA: a new method for scalable model-free online change-point detection N Keriven, D Garreau, I Poli IEEE Transactions on Signal Processing 68, 3515-3528, 2020 | 48 | 2020 |
| Principled Training of Neural Networks with Direct Feedback Alignment J Launay, I Poli, F Krzakala arXiv preprint arXiv:1906.04554, 2019 | 39 | 2019 |
| Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment J Launay, I Poli, K Müller, G Pariente, I Carron, L Daudet, F Krzakala, ... arXiv preprint arXiv:2012.06373, 2020 | 19 | 2020 |
| Adversarial robustness by design through analog computing and synthetic gradients A Cappelli, R Ohana, J Launay, L Meunier, I Poli, F Krzakala ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 13 | 2022 |
| Photonic Differential Privacy with Direct Feedback Alignment R Ohana, H Medina, J Launay, A Cappelli, I Poli, L Ralaivola, ... Advances in Neural Information Processing Systems 34, 2021 | 12 | 2021 |
| LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor C Brossollet, A Cappelli, I Carron, C Chaintoutis, A Chatelain, L Daudet, ... arXiv preprint arXiv:2107.11814, 2021 | 11 | 2021 |
| Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra D Hesslow, A Cappelli, I Carron, L Daudet, R Lafargue, K Müller, ... arXiv preprint arXiv:2104.14429, 2021 | 10 | 2021 |
| PAGnol: An Extra-Large French Generative Model J Launay, EL Tommasone, B Pannier, F Boniface, A Chatelain, A Cappelli, ... arXiv preprint arXiv:2110.08554, 2021 | 9 | 2021 |
| Method and system for machine learning using optical data I Poli, J Launay, K Müller, G Pariente, I Carron, L Daudet US Patent 11,137,289, 2021 | 7 | 2021 |
| ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients A Cappelli, R Ohana, J Launay, L Meunier, I Poli ICML 2021 Workshop on Adversarial Machine Learning, 2021 | 7 | 2021 |
| Light-in-the-loop: using a photonics co-processor for scalable training of neural networks J Launay, I Poli, K Müller, I Carron, L Daudet, F Krzakala, S Gigan arXiv preprint arXiv:2006.01475, 2020 | 7 | 2020 |
| Is the Number of Trainable Parameters All That Actually Matters? A Chatelain, A Djeghri, D Hesslow, J Launay I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 27-32, 2022 | 6 | 2022 |
| Contrastive Embeddings for Neural Architectures D Hesslow, I Poli arXiv preprint arXiv:2102.04208, 2021 | 6 | 2021 |
| Method and system for distributed training using synthetic gradients J Launay, I Poli, K Müller, G Pariente, I Carron, L Daudet US Patent App. 17/117,925, 2022 | 2 | 2022 |
| Binarization for Optical Processing Units via REINFORCE B Kozyrskiy, I Poli, R Ohana, L Daudet, I Carron, M Filippone Proceedings of the 3rd International Conference on Advances in Signal …, 2021 | 1* | 2021 |
| Online Change Point Detection in Molecular Dynamics With Optical Random Features A Chatelain, E Tommasone, L Daudet, I Poli arXiv preprint arXiv:2006.08697, 2020 | 1 | 2020 |
| Learning Binary Data Representation for Optical Processing Units B Kozyrskiy, M Filippone, I Poli, R Ohana, L Daudet, I Carron Sensors & Transducers 256 (2), 1-11, 2022 | | 2022 |
| METHOD AND SYSTEM FOR MACHINE LEARNING USING OPTICAL DATA I Poli, J Launay, K Müller, G Pariente, I Carron, L Daudet, R Ohana, ... US Patent App. 17/331,240, 2021 | | 2021 |
