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 | 504 | 2019 |
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 | 381 | 2020 |
A White Paper on Neural Network Quantization M Nagel, M Fournarakis, RA Amjad, Y Bondarenko, M van Baalen, ... arXiv preprint arXiv:2106.08295, 2021 | 330 | 2021 |
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 | 202 | 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 | 107 | 2020 |
Understanding and Overcoming the Challenges of Efficient Transformer Quantization Y Bondarenko, M Nagel, T Blankevoort arXiv preprint arXiv:2109.12948, 2021 | 86 | 2021 |
Overcoming Oscillations in Quantization-Aware Training M Nagel, M Fournarakis, Y Bondarenko, T Blankevoort International Conference on Machine Learning, 16318-16330, 2022 | 51 | 2022 |
Implicit Neural Video Compression Y Zhang, T van Rozendaal, J Brehmer, M Nagel, T Cohen arXiv preprint arXiv:2112.11312, 2021 | 41 | 2021 |
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 | 40 | 2022 |
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 | 39 | 2012 |
Event Fisher Vectors: Robust Encoding Visual Diversity of Visual Streams. M Nagel, T Mensink, CGM Snoek BMVC 2, 6, 2015 | 31 | 2015 |
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 | 26 | 2022 |
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 | 21 | 2019 |
Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing Y Bondarenko, M Nagel, T Blankevoort Advances in Neural Information Processing Systems 36, 2023 | 18 | 2023 |
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 | 12 | 2022 |
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 | 11 | 2023 |
Simulated Quantization, Real Power Savings M van Baalen, B Kahne, E Mahurin, A Kuzmin, A Skliar, M Nagel, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 8 | 2022 |
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 | 7 | 2023 |
A Practical Mixed Precision Algorithm for Post-Training Quantization NP Pandey, M Nagel, M van Baalen, Y Huang, C Patel, T Blankevoort arXiv preprint arXiv:2302.05397, 2023 | 7 | 2023 |
Quadapter: Adapter for GPT-2 Quantization M Park, J You, M Nagel, S Chang arXiv preprint arXiv:2211.16912, 2022 | 6 | 2022 |