Mark Collier

According to our database, Mark Collier authored at least 22 papers between 2018 and 2026.

Collaborative distances:

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

2026

Semantic Document Derendering: SVG Reconstruction via Vision-Language Modeling.

Adam Hazimeh, Ke Wang, Mark Collier, Gilles Baechler, Efi Kokiopoulou, Pascal Frossard

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Sketch-to-Layout: Sketch-Guided Multimodal Layout Generation.

Riccardo Brioschi, Aleksandr Alekseev, Emanuele Nevali, Berkay Döner, Omar El Malki, Blagoj Mitrevski, Leandro Kieliger, Mark Collier, Andrii Maksai, Jesse Berent, Claudiu Cristian Musat, Efi Kokiopoulou

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

2024

Pretrained Visual Uncertainties.

Michael Kirchhof, Mark Collier, Seong Joon Oh, Enkelejda Kasneci

CoRR, 2024

Representing Online Handwriting for Recognition in Large Vision-Language Models.

Anastasiia Fadeeva, Philippe Schlattner, Andrii Maksai, Mark Collier, Efi Kokiopoulou, Jesse Berent, Claudiu Musat

CoRR, 2024

Pi-DUAL: Using privileged information to distinguish clean from noisy labels.

Ke Wang, Guillermo Ortiz-Jiménez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Three Towers: Flexible Contrastive Learning with Pretrained Image Models.

Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

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

When does Privileged information Explain Away Label Noise?

Guillermo Ortiz-Jiménez, Mark Collier, Anant Nawalgaria, Alexander Nicholas D'Amour, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou

Proceedings of the International Conference on Machine Learning, 2023

Scaling Vision Transformers to 22 Billion Parameters.

Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby

Proceedings of the International Conference on Machine Learning, 2023

Massively Scaling Heteroscedastic Classifiers.

Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Deep Classifiers with Label Noise Modeling and Distance Awareness.

Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Trans. Mach. Learn. Res., 2022

Plex: Towards Reliability using Pretrained Large Model Extensions.

Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

CoRR, 2022

Transfer and Marginalize: Explaining Away Label Noise with Privileged Information.

Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou, Jesse Berent

Proceedings of the International Conference on Machine Learning, 2022

2021

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.

Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran

CoRR, 2021

Correlated Input-Dependent Label Noise in Large-Scale Image Classification.

Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Routing Networks with Co-training for Continual Learning.

Mark Collier, Efi Kokiopoulou, Andrea Gesmundo, Jesse Berent

CoRR, 2020

VAEs in the Presence of Missing Data.

Mark Collier, Alfredo Nazábal, Christopher K. I. Williams

CoRR, 2020

Analysis of Softmax Approximation for Deep Classifiers under Input-Dependent Label Noise.

Mark Collier, Basil Mustafa, Efi Kokiopoulou, Jesse Berent

CoRR, 2020

2019

Scalable Deep Unsupervised Clustering with Concrete GMVAEs.

Mark Collier, Hector Urdiales

CoRR, 2019

Memory-Augmented Neural Networks for Machine Translation.

Mark Collier, Joeran Beel

Proceedings of Machine Translation Summit XVII Volume 1: Research Track, 2019

2018

Deep Contextual Multi-armed Bandits.

Mark Collier, Hector Urdiales Llorens

CoRR, 2018

Implementing Neural Turing Machines.

Mark Collier, Jöran Beel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

An Empirical Comparison of Syllabuses for Curriculum Learning.

Mark Collier, Jöran Beel

Proceedings of the Proceedings for the 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science Trinity College Dublin, 2018