Mart van Baalen

According to our database, Mart van Baalen authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

GPTVQ: The Blessing of Dimensionality for LLM Quantization.

Mart van Baalen, Andrey Kuzmin, Markus Nagel, Peter Couperus, Cédric Bastoul, Eric Mahurin, Tijmen Blankevoort, Paul N. Whatmough

CoRR, 2024

2023

The LLM Surgeon.

Tycho F. A. van der Ouderaa, Markus Nagel, Mart van Baalen, Yuki M. Asano, Tijmen Blankevoort

CoRR, 2023

FP8 versus INT8 for efficient deep learning inference.

Mart van Baalen, Andrey Kuzmin, Suparna S. Nair, Yuwei Ren, Eric Mahurin, Chirag Patel, Sundar Subramanian, Sanghyuk Lee, Markus Nagel, Joseph Soriaga, Tijmen Blankevoort

CoRR, 2023

Pruning vs Quantization: Which is Better?

Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

QBitOpt: Fast and Accurate Bitwidth Reallocation during Training.

Jorn Peters, Marios Fournarakis, Markus Nagel, Mart van Baalen, Tijmen Blankevoort

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Practical Mixed Precision Algorithm for Post-Training Quantization.

Nilesh Prasad Pandey, Markus Nagel, Mart van Baalen, Yin Huang, Chirag Patel, Tijmen Blankevoort

Proceedings of the 34th British Machine Vision Conference Workshop Proceedings, 2023

2022

Quantized Sparse Weight Decomposition for Neural Network Compression.

Andrey Kuzmin, Mart van Baalen, Markus Nagel, Arash Behboodi

CoRR, 2022

FP8 Quantization: The Power of the Exponent.

Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Cyclical Pruning for Sparse Neural Networks.

Suraj Srinivas, Andrey Kuzmin, Markus Nagel, Mart van Baalen, Andrii Skliar, Tijmen Blankevoort

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Simulated Quantization, Real Power Savings.

Mart van Baalen, Brian Kahne, Eric Mahurin, Andrey Kuzmin, Andrii Skliar, Markus Nagel, Tijmen Blankevoort

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

A White Paper on Neural Network Quantization.

Markus Nagel, Marios Fournarakis, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, Tijmen Blankevoort

CoRR, 2021

2020

Gradient 𝓁₁ Regularization for Quantization Robustness.

Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling

CoRR, 2020

Bayesian Bits: Unifying Quantization and Pruning.

Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Up or Down? Adaptive Rounding for Post-Training Quantization.

Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort

Proceedings of the 37th International Conference on Machine Learning, 2020

Gradient $\ell_1$ Regularization for Quantization Robustness.

Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Data-Free Quantization Through Weight Equalization and Bias Correction.

Markus Nagel, Mart van Baalen, Tijmen Blankevoort, Max Welling

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019