Neil Houlsby

According to our database, Neil Houlsby authored at least 72 papers between 2011 and 2024.

Collaborative distances:

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

2024

Frozen Feature Augmentation for Few-Shot Image Classification.

Andreas Bär, Neil Houlsby, Mostafa Dehghani, Manoj Kumar

CoRR, 2024

Location-Aware Self-Supervised Transformers for Semantic Segmentation.

Mathilde Caron, Neil Houlsby, Cordelia Schmid

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Dual PatchNorm.

Manoj Kumar, Mostafa Dehghani, Neil Houlsby

Trans. Mach. Learn. Res., 2023

Scaling Laws for Sparsely-Connected Foundation Models.

Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci

CoRR, 2023

From Sparse to Soft Mixtures of Experts.

Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Neil Houlsby

CoRR, 2023

PaLI-X: On Scaling up a Multilingual Vision and Language Model.

Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

CoRR, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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

CoRR, 2023

Image Captioners Are Scalable Vision Learners Too.

Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer

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

Scaling Open-Vocabulary Object Detection.

Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby

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

Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution.

Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby

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

Adaptive Computation with Elastic Input Sequence.

Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You

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

UL2: Unifying Language Learning Paradigms.

Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Denny Zhou, Neil Houlsby, Donald Metzler

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints.

Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby

Proceedings of the Eleventh International Conference on Learning Representations, 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

Transcending Scaling Laws with 0.1% Extra Compute.

Yi Tay, Jason Wei, Hyung Won Chung, Vinh Q. Tran, David R. So, Siamak Shakeri, Xavier Garcia, Huaixiu Steven Zheng, Jinfeng Rao, Aakanksha Chowdhery, Denny Zhou, Donald Metzler, Slav Petrov, Neil Houlsby, Quoc V. Le, Mostafa Dehghani

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

CLIPPO: Image-and-Language Understanding from Pixels Only.

Michael Tschannen, Basil Mustafa, Neil Houlsby

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Do better ImageNet classifiers assess perceptual similarity better?

Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin Dogus Cubuk

Trans. Mach. Learn. Res., 2022

Sparse MoEs meet Efficient Ensembles.

James Urquhart Allingham, Florian Wenzel, Zelda E. Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

Trans. Mach. Learn. Res., 2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.

Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

J. Mach. Learn. Res., 2022

Image-and-Language Understanding from Pixels Only.

Michael Tschannen, Basil Mustafa, Neil Houlsby

CoRR, 2022

Location-Aware Self-Supervised Transformers.

Mathilde Caron, Neil Houlsby, Cordelia Schmid

CoRR, 2022

PaLI: A Jointly-Scaled Multilingual Language-Image Model.

Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.

Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, Yuan Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zachary Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Gregory S. Corrado, Dale R. Webster, David J. Fleet, Geoffrey E. Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan

CoRR, 2022

Simple Open-Vocabulary Object Detection with Vision Transformers.

Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby

CoRR, 2022

Unifying Language Learning Paradigms.

Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, Donald Metzler

CoRR, 2022

On the surprising tradeoff between ImageNet accuracy and perceptual similarity.

Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin D. Cubuk

CoRR, 2022

Learning to Merge Tokens in Vision Transformers.

Cédric Renggli, André Susano Pinto, Neil Houlsby, Basil Mustafa, Joan Puigcerver, Carlos Riquelme

CoRR, 2022

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts.

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

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

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.

Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby

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

Simple Open-Vocabulary Object Detection.

Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby

Proceedings of the Computer Vision - ECCV 2022, 2022

Scaling Vision Transformers.

Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer

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

2021

Guest Editorial: Automated Machine Learning.

Hugo Jair Escalante, Quanming Yao, Wei-Wei Tu, Nelishia Pillay, Rong Qu, Yang Yu, Neil Houlsby

IEEE Trans. Pattern Anal. Mach. Intell., 2021

The Benchmark Lottery.

Mostafa Dehghani, Yi Tay, Alexey A. Gritsenko, Zhe Zhao, Neil Houlsby, Fernando Diaz, Donald Metzler, Oriol Vinyals

CoRR, 2021

SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size.

Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai

CoRR, 2021

Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

CoRR, 2021

Supervised Transfer Learning at Scale for Medical Imaging.

Basil Mustafa, Aaron Loh, Jan Freyberg, Patricia MacWilliams, Megan Wilson, Scott Mayer McKinney, Marcin Sieniek, Jim Winkens, Yuan Liu, Peggy Bui, Shruthi Prabhakara, Umesh Telang, Alan Karthikesalingam, Neil Houlsby, Vivek Natarajan

CoRR, 2021

Representation learning from videos in-the-wild: An object-centric approach.

Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

MLP-Mixer: An all-MLP Architecture for Vision.

Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scaling Vision with Sparse Mixture of Experts.

Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting the Calibration of Modern Neural Networks.

Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches.

Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Scalable Transfer Learning with Expert Models.

Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby

Proceedings of the 9th International Conference on Learning Representations, 2021

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby

Proceedings of the 9th International Conference on Learning Representations, 2021

On Robustness and Transferability of Convolutional Neural Networks.

Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic

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

2020

Deep Ensembles for Low-Data Transfer Learning.

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto, Daniel Keysers, Neil Houlsby

CoRR, 2020

Training General Representations for Remote Sensing Using in-Domain Knowledge.

Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Automatic Shortcut Removal for Self-Supervised Representation Learning.

Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen

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

Big Transfer (BiT): General Visual Representation Learning.

Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby

Proceedings of the Computer Vision - ECCV 2020, 2020

Self-Supervised Learning of Video-Induced Visual Invariances.

Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Large Scale Learning of General Visual Representations for Transfer.

Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby

CoRR, 2019

In-domain representation learning for remote sensing.

Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby

CoRR, 2019

The Visual Task Adaptation Benchmark.

Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby

CoRR, 2019

Parameter-Efficient Transfer Learning for NLP.

Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly

Proceedings of the 36th International Conference on Machine Learning, 2019

On Self Modulation for Generative Adversarial Networks.

Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly

Proceedings of the 7th International Conference on Learning Representations, 2019

Self-Supervised GANs via Auxiliary Rotation Loss.

Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Neural Architecture Search Over a Graph Search Space.

Quentin de Laroussilhe, Stanislaw Jastrzebski, Neil Houlsby, Andrea Gesmundo

CoRR, 2018

Self-Supervised Generative Adversarial Networks.

Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby

CoRR, 2018

Self-Supervised GAN to Counter Forgetting.

Ting Chen, Xiaohua Zhai, Neil Houlsby

CoRR, 2018

Transfer Automatic Machine Learning.

Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo

CoRR, 2018

Analyzing Language Learned by an Active Question Answering Agent.

Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang

CoRR, 2018

Transfer Learning with Neural AutoML.

Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Ask the Right Questions: Active Question Reformulation with Reinforcement Learning.

Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang

Proceedings of the 6th International Conference on Learning Representations, 2018

2014

A Filtering Approach to Stochastic Variational Inference.

Neil Houlsby, David M. Blei

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Cold-start Active Learning with Robust Ordinal Matrix Factorization.

Neil Houlsby, José Miguel Hernández-Lobato, Zoubin Ghahramani

Proceedings of the 31th International Conference on Machine Learning, 2014

Probabilistic Matrix Factorization with Non-random Missing Data.

José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani

Proceedings of the 31th International Conference on Machine Learning, 2014

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices.

José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani

Proceedings of the 31th International Conference on Machine Learning, 2014

A Scalable Gibbs Sampler for Probabilistic Entity Linking.

Neil Houlsby, Massimiliano Ciaramita

Proceedings of the Advances in Information Retrieval, 2014

2013

Scalable Probabilistic Entity-Topic Modeling.

Neil Houlsby, Massimiliano Ciaramita

CoRR, 2013

Active Learning for Interactive Visualization.

Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Collaborative Gaussian Processes for Preference Learning.

Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Bayesian Active Learning for Classification and Preference Learning

Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel

CoRR, 2011