| Data-Free Quantization through Weight Equalization and Bias Correction M Nagel, M Baalen, T Blankevoort, M Welling Proceedings of the IEEE International Conference on Computer Vision, 1325-1334, 2019 | 587 | 2019 |
| A White Paper on Neural Network Quantization M Nagel, M Fournarakis, RA Amjad, Y Bondarenko, M van Baalen, ... arXiv preprint arXiv:2106.08295, 2021 | 545 | 2021 |
| Up or Down? Adaptive Rounding for Post-Training Quantization M Nagel, RA Amjad, M van Baalen, C Louizos, T Blankevoort Proceedings of the 37th International Conference on Machine Learning, 2020 | 522 | 2020 |
| LSQ+: Improving low-bit quantization through learnable offsets and better initialization Y Bhalgat, J Lee, M Nagel, T Blankevoort, N Kwak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 243 | 2020 |
| Bayesian bits: Unifying quantization and pruning M Van Baalen, C Louizos, M Nagel, RA Amjad, Y Wang, T Blankevoort, ... Advances in neural information processing systems 33, 5741-5752, 2020 | 136 | 2020 |
| Understanding and Overcoming the Challenges of Efficient Transformer Quantization Y Bondarenko, M Nagel, T Blankevoort arXiv preprint arXiv:2109.12948, 2021 | 130 | 2021 |
| Overcoming Oscillations in Quantization-Aware Training M Nagel, M Fournarakis, Y Bondarenko, T Blankevoort International Conference on Machine Learning, 16318-16330, 2022 | 91 | 2022 |
| Fp8 quantization: The power of the exponent A Kuzmin, M Van Baalen, Y Ren, M Nagel, J Peters, T Blankevoort Advances in Neural Information Processing Systems 35, 14651-14662, 2022 | 65 | 2022 |
| Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing Y Bondarenko, M Nagel, T Blankevoort Advances in Neural Information Processing Systems 36, 2023 | 63 | 2023 |
| Implicit Neural Video Compression Y Zhang, T van Rozendaal, J Brehmer, M Nagel, T Cohen arXiv preprint arXiv:2112.11312, 2021 | 56 | 2021 |
| Beam Loss Monitoring for LHC Machine Protection EB Holzer, B Dehning, E Effnger, J Emery, V Grishin, C Hajdu, S Jackson, ... Physics Procedia 37, 2055-2062, 2012 | 41 | 2012 |
| Pruning vs Quantization: Which is Better? A Kuzmin, M Nagel, M Van Baalen, A Behboodi, T Blankevoort Advances in Neural Information Processing Systems 36, 2023 | 35 | 2023 |
| Neural Network Quantization with AI Model Efficiency Toolkit (AIMET) S Siddegowda, M Fournarakis, M Nagel, T Blankevoort, C Patel, ... arXiv preprint arXiv:2201.08442, 2022 | 34 | 2022 |
| Event Fisher Vectors: Robust Encoding Visual Diversity of Visual Streams. M Nagel, T Mensink, CGM Snoek BMVC 2, 6, 2015 | 31 | 2015 |
| FP8 versus INT8 for efficient deep learning inference M van Baalen, A Kuzmin, SS Nair, Y Ren, E Mahurin, C Patel, ... arXiv preprint arXiv:2303.17951, 2023 | 30 | 2023 |
| Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks A Kuzmin, M Nagel, S Pitre, S Pendyam, T Blankevoort, M Welling arXiv preprint arXiv:1912.09802, 2019 | 25 | 2019 |
| Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices K Gupta, M Fournarakis, M Reisser, C Louizos, M Nagel arXiv preprint arXiv:2206.10844, 2022 | 16 | 2022 |
| Cyclical Pruning for Sparse Neural Networks S Srinivas, A Kuzmin, M Nagel, M van Baalen, A Skliar, T Blankevoort Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| The LLM Surgeon TFA van der Ouderaa, M Nagel, M van Baalen, YM Asano, T Blankevoort The Twelfth International Conference on Learning Representations (ICLR), 2023 | 15 | 2023 |
| GPTVQ: The Blessing of Dimensionality for LLM Quantization M van Baalen, A Kuzmin, M Nagel, P Couperus, C Bastoul, E Mahurin, ... arXiv preprint arXiv:2402.15319, 2024 | 11 | 2024 |
Tijmen BlankevoortMeta Reality Labs確認したメール アドレス: qti.qualcomm.com