Data-Free Quantization Through Weight Equalization and Bias Correction. - Markus Nagel; Mart van Baalen; Tijmen Blankevoort; Max Welling (ICCV, 2019)

Gradient $ ell_1$ Regularization for Quantization Robustness. - Milad Alizadeh; Arash Behboodi; Mart van Baalen; Christos Louizos; Tijmen Blankevoort; Max Welling (ICLR, 2020)

Up or Down? Adaptive Rounding for Post-Training Quantization. - Markus Nagel; Rana Ali Amjad; Mart van Baalen; Christos Louizos; Tijmen Blankevoort (ICML, 2020)

Bayesian Bits: Unifying Quantization and Pruning. - Mart van Baalen; Christos Louizos; Markus Nagel; Rana Ali Amjad; Ying Wang 051; Tijmen Blankevoort; Max Welling (NeurIPS, 2020)

Gradient 𝓁1 Regularization for Quantization Robustness. - Milad Alizadeh; Arash Behboodi; Mart van Baalen; Christos Louizos; Tijmen Blankevoort; Max Welling (CoRR, 2020)

A White Paper on Neural Network Quantization. - Markus Nagel; Marios Fournarakis; Rana Ali Amjad; Yelysei Bondarenko; Mart van Baalen; Tijmen Blankevoort (CoRR, 2021)

Simulated Quantization, Real Power Savings. - Mart van Baalen; Brian Kahne; Eric Mahurin; Andrey Kuzmin; Andrii Skliar; Markus Nagel; Tijmen Blankevoort (CVPR Workshops, 2022)

Cyclical Pruning for Sparse Neural Networks. - Suraj Srinivas; Andrey Kuzmin; Markus Nagel; Mart van Baalen; Andrii Skliar; Tijmen Blankevoort (CVPR Workshops, 2022)

FP8 Quantization: The Power of the Exponent. - Andrey Kuzmin; Mart van Baalen; Yuwei Ren; Markus Nagel; Jorn Peters; Tijmen Blankevoort (NeurIPS, 2022)

Quantized Sparse Weight Decomposition for Neural Network Compression. - Andrey Kuzmin; Mart van Baalen; Markus Nagel; Arash Behboodi (CoRR, 2022)

A Practical Mixed Precision Algorithm for Post-Training Quantization. - Nilesh Prasad Pandey; Markus Nagel; Mart van Baalen; Yin Huang; Chirag Patel; Tijmen Blankevoort (BMVC Workshop, 2023)

QBitOpt: Fast and Accurate Bitwidth Reallocation during Training. - Jorn Peters; Marios Fournarakis; Markus Nagel; Mart van Baalen; Tijmen Blankevoort (ICCV (Workshops), 2023)

Pruning vs Quantization: Which is Better? - Andrey Kuzmin; Markus Nagel; Mart van Baalen; Arash Behboodi; Tijmen Blankevoort (NeurIPS, 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)

The LLM Surgeon. - Tycho F. A. van der Ouderaa; Markus Nagel; Mart van Baalen; Yuki M. Asano; Tijmen Blankevoort (CoRR, 2023)

The LLM Surgeon. - Tycho F. A. van der Ouderaa; Markus Nagel; Mart van Baalen; Tijmen Blankevoort (ICLR, 2024)

Sparse High Rank Adapters. - Kartikeya Bhardwaj; Nilesh Prasad Pandey; Sweta Priyadarshi; Viswanath Ganapathy; Shreya Kadambi; Rafael Esteves 002; Shubhankar Borse; Paul N. Whatmough; Risheek Garrepalli; Mart van Baalen; Harris Teague; Markus Nagel (NeurIPS, 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)

Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters. - Kartikeya Bhardwaj; Nilesh Prasad Pandey; Sweta Priyadarshi; Viswanath Ganapathy; Rafael Esteves 002; Shreya Kadambi; Shubhankar Borse; Paul N. Whatmough; Risheek Garrepalli; Mart van Baalen; Harris Teague; Markus Nagel (CoRR, 2024)

Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking. - Marco Federici; Davide Belli; Mart van Baalen; Amir Jalalirad; Andrii Skliar; Bence Major; Markus Nagel; Paul N. Whatmough (CoRR, 2024)

Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference. - Andrii Skliar; Ties van Rozendaal; Romain Lepert; Todor Boinovski; Mart van Baalen; Markus Nagel; Paul N. Whatmough; Babak Ehteshami Bejnordi (Trans. Mach. Learn. Res., 2025)