| Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs A Rajagopal, DA Vink, SI Venieris, CS Bouganis Published at ICML 2020, 2020 | 17 | 2020 |
| Caffe Barista: Brewing Caffe with FPGAs in the Training Loop DA Vink, A Rajagopal, SI Venieris, CS Bouganis Published as a short paper at FPL 2020, 2020 | 6 | 2020 |
| perf4sight: A toolflow to model CNN training performance on Edge GPUs A Rajagopal, CS Bouganis Proceedings of the IEEE/CVF International Conference on Computer Vision, 963-971, 2021 | 4 | 2021 |
| Now that I can see, I can improve: Enabling data-driven finetuning of CNNs on the edge A Rajagopal, CS Bouganis Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 3 | 2020 |
| GSA to HDL: Towards principled generation of dynamically scheduled circuits A Rajagopal, DA Vink, J Cheng, Y Herklotz arXiv preprint arXiv:2308.11048, 2023 | | 2023 |
| Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices A Rajagopal, CS Bouganis arXiv preprint arXiv:2203.00772, 2022 | | 2022 |
| Enabling on-device domain adaptation of convolutional neural networks A Rajagopal Imperial College London, 2022 | | 2022 |
| intelligent Digital Systems Lab A Montgomerie, D Vink, A Rajagopal | | |
Christos BouganisImperial College LondonVerified email at ic.ac.uk
