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

Relaxed Quantization for Discretized Neural Networks. - Christos Louizos; Matthias Reisser; Tijmen Blankevoort; Efstratios Gavves; Max Welling (ICLR (Poster), 2019)

Batch-Shaped Channel Gated Networks. - Babak Ehteshami Bejnordi; Tijmen Blankevoort; Max Welling (CoRR, 2019)

Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks. - Andrey Kuzmin; Markus Nagel; Saurabh Pitre; Sandeep Pendyam; Tijmen Blankevoort; Max Welling (CoRR, 2019)

Conditional Channel Gated Networks for Task-Aware Continual Learning. - Davide Abati; Jakub Tomczak; Tijmen Blankevoort; Simone Calderara; Rita Cucchiara; Babak Ehteshami Bejnordi (CVPR, 2020)

LSQ+: Improving low-bit quantization through learnable offsets and better initialization. - Yash Bhalgat; Jinwon Lee; Markus Nagel; Tijmen Blankevoort; Nojun Kwak (CVPR Workshops, 2020)

Differentiable Joint Pruning and Quantization for Hardware Efficiency. - Ying Wang 051; Yadong Lu; Tijmen Blankevoort (ECCV (29), 2020)

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

Batch-shaping for learning conditional channel gated networks. - Babak Ehteshami Bejnordi; 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)

Learned Threshold Pruning. - Kambiz Azarian; Yash Bhalgat; Jinwon Lee; Tijmen Blankevoort (CoRR, 2020)

Understanding and Overcoming the Challenges of Efficient Transformer Quantization. - Yelysei Bondarenko; Markus Nagel; Tijmen Blankevoort (EMNLP (1), 2021)

Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces. - Bert Moons; Parham Noorzad; Andrii Skliar; Giovanni Mariani; Dushyant Mehta; Chris Lott; Tijmen Blankevoort (ICCV, 2021)

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

Revisiting single-gated Mixtures of Experts. - Amelie Royer; Ilia Karmanov; Andrii Skliar; Babak Ehteshami Bejnordi; Tijmen Blankevoort (BMVC, 2022)

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

Simple and Efficient Architectures for Semantic Segmentation. - Dushyant Mehta; Andrii Skliar; Haitam Ben Yahia; Shubhankar Borse; Fatih Porikli; Amirhossein Habibian; 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)

Overcoming Oscillations in Quantization-Aware Training. - Markus Nagel; Marios Fournarakis; Yelysei Bondarenko; Tijmen Blankevoort (ICML, 2022)

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

Neural Network Quantization with AI Model Efficiency Toolkit (AIMET). - Sangeetha Siddegowda; Marios Fournarakis; Markus Nagel; Tijmen Blankevoort; Chirag Patel; Abhijit Khobare (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)

Efficient Neural PDE-Solvers using Quantization Aware Training. - Winfried van den Dool; Tijmen Blankevoort; Max Welling; Yuki M. Asano (ICCV (Workshops), 2023)

MSViT: Dynamic Mixed-scale Tokenization for Vision Transformers. - Jakob Drachmann Havtorn; Amélie Royer; Tijmen Blankevoort; Babak Ehteshami Bejnordi (ICCV (Workshops), 2023)

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

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing. - Yelysei Bondarenko; Markus Nagel; Tijmen Blankevoort (NeurIPS, 2023)

Pruning vs Quantization: Which is Better? - Andrey Kuzmin; Markus Nagel; Mart van Baalen; Arash Behboodi; Tijmen Blankevoort (NeurIPS, 2023)

Scalarization for Multi-Task and Multi-Domain Learning at Scale. - Amelie Royer; Tijmen Blankevoort; Babak Ehteshami Bejnordi (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)

InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning. - Babak Ehteshami Bejnordi; Gaurav Kumar; Amelie Royer; Christos Louizos; Tijmen Blankevoort; Mohsen Ghafoorian (BMVC, 2024)

VeRA: Vector-based Random Matrix Adaptation. - Dawid Jan Kopiczko; Tijmen Blankevoort; Yuki M. Asano (ICLR, 2024)

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

Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding. - Benjamin Bergner; Andrii Skliar; Amelie Royer; Tijmen Blankevoort; Yuki M. Asano; Babak Ehteshami Bejnordi (CoRR, 2024)

Bitune: Bidirectional Instruction-Tuning. - Dawid Jan Kopiczko; Tijmen Blankevoort; Yuki M. Asano (CoRR, 2024)

Llama Guard 3-1B-INT4: Compact and Efficient Safeguard for Human-AI Conversations. - Igor Fedorov; Kate Plawiak; Lemeng Wu; Tarek Elgamal; Naveen Suda; Eric Smith; Hongyuan Zhan; Jianfeng Chi; Yuriy Hulovatyy; Kimish Patel; Zechun Liu; Changsheng Zhao 002; et al. (CoRR, 2024)

SpinQuant: LLM Quantization with Learned Rotations. - Zechun Liu; Changsheng Zhao 002; Igor Fedorov; Bilge Soran; Dhruv Choudhary; Raghuraman Krishnamoorthi; Vikas Chandra; Yuandong Tian; Tijmen Blankevoort (ICLR, 2025)

ParetoQ: Scaling Laws in Extremely Low-bit LLM Quantization. - Zechun Liu; Changsheng Zhao 002; Hanxian Huang; Sijia Chen; Jing Zhang; Jiawei Zhao; Scott Roy; Lisa Jin; Yunyang Xiong; Yangyang Shi; Lin Xiao; Yuandong Tian; et al. (CoRR, 2025)