Risk management for a robot-assisted needle positioning system for interventional radiology. - Markus Nagel; Gerd Schmidt; Gero Schnütgen; Willi A. Kalender (CARS, 2004)

A Navigation System for Minimally Invasive CT-Guided Interventions. - Markus Nagel; Gerd Schmidt; Ralf Petzold; Willi A. Kalender (MICCAI (2), 2005)

IGS (Image Guided Surgery) - Phantomversuche und erste klinische Erfahrungen mit einem neuartigen CT-basierten Navigationssystem. - Ulrich H. W. Krause; Markus Nagel; Rainer Seibel (Bildverarbeitung für die Medizin, 2006)

Rawdata-Based Detection of the Optimal Reconstruction Phase in ECG-Gated Cardiac Image Reconstruction. - Dirk Ertel; Marc Kachelriess; Tobias Pflederer; Stephan Achenbach; Robert M. Lapp; Markus Nagel; Willi A. Kalender (MICCAI (2), 2006)

Needle and catheter navigation using electromagnetic tracking for computer-assisted C-arm CT interventions. - Markus Nagel; Martin Hoheisel; Ralf Petzold; Willi A. Kalender; Ulrich H. W. Krause (Image-Guided Procedures, 2007)

Electromagnetic tracking system for minimal invasive interventions using a C-arm system with CT option: first clinical results. - Markus Nagel; Martin Hoheisel; Ulrich Bill; Klaus Klingenbeck-Regn; Willi A. Kalender; Ralf Petzold (Image-Guided Procedures, 2008)

Event Fisher Vectors: Robust Encoding Visual Diversity of Visual Streams. - Markus Nagel; Thomas Mensink; Cees G. M. Snoek (BMVC, 2015)

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

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

In-Hindsight Quantization Range Estimation for Quantized Training. - Marios Fournarakis; Markus Nagel (CVPR Workshops, 2021)

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

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

Implicit Neural Video Compression. - Yunfan Zhang; Ties van Rozendaal; Johann Brehmer; Markus Nagel; Taco Cohen (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)

Quadapter: Adapter for GPT-2 Quantization. - Minseop Park; Jaeseong You; Markus Nagel; Simyung Chang (EMNLP (Findings), 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)

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)

ResQ: Residual Quantization for Video Perception. - Davide Abati; Haitam Ben Yahia; Markus Nagel; Amirhossein Habibian (ICCV, 2023)

Softmax Bias Correction for Quantized Generative Models. - Nilesh Prasad Pandey; Marios Fournarakis; Chirag Patel; Markus Nagel (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)

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)

Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. - Kartik Gupta; Marios Fournarakis; Matthias Reisser; Christos Louizos; Markus Nagel (Trans. Mach. Learn. Res., 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)

MobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device. - Ties van Rozendaal; Tushar Singhal; Hoang Le; Guillaume Sautière; Amir Said; Krishna Buska; Anjuman Raha; Dimitris Kalatzis; Hitarth Mehta; Frank Mayer; Liang Zhang; Markus Nagel; et al. (WACV, 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)

How to Parameterize Asymmetric Quantization Ranges for Quantization-Aware Training. - Jaeseong You; Minseop Park; Kyunggeun Lee; Seokjun An; Chirag Patel; Markus Nagel (CoRR, 2024)

Low-Rank Quantization-Aware Training for LLMs. - Yelysei Bondarenko; Riccardo Del Chiaro; Markus Nagel (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)

FPTQuant: Function-Preserving Transforms for LLM Quantization. - Boris van Breugel; Yelysei Bondarenko; Paul N. Whatmough; Markus Nagel (CoRR, 2025)

HadaNorm: Diffusion Transformer Quantization through Mean-Centered Transformations. - Marco Federici; Riccardo Del Chiaro; Boris van Breugel; Paul N. Whatmough; Markus Nagel (CoRR, 2025)