Neil Houlsby

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 87

Top Topics

Matrix Factorization

Object Detection

Top Venues

Publications

Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You
Adaptive Computation with Elastic Input Sequence. CoRR (2023)
Manoj Kumar, Mostafa Dehghani, Neil Houlsby
Dual PatchNorm. Trans. Mach. Learn. Res. 2023 (2023)
Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You
Adaptive Computation with Elastic Input Sequence. ICML (2023)
Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby
Scaling Open-Vocabulary Object Detection. NeurIPS (2023)
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
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS (2023)
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 Le, Mostafa Dehghani
Transcending Scaling Laws with 0.1% Extra Compute. EMNLP (2023)
Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou
Massively Scaling Heteroscedastic Classifiers. CoRR (2023)
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
UL2: Unifying Language Learning Paradigms. ICLR (2023)
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 Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
Scaling Vision Transformers to 22 Billion Parameters. CoRR (2023)
Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints. ICLR (2023)
Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby
Scaling Open-Vocabulary Object Detection. CoRR (2023)
Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
Image Captioners Are Scalable Vision Learners Too. NeurIPS (2023)
Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci
Scaling Laws for Sparsely-Connected Foundation Models. CoRR (2023)
Manoj Kumar, Mostafa Dehghani, Neil Houlsby
Dual PatchNorm. CoRR (2023)
Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou
Massively Scaling Heteroscedastic Classifiers. ICLR (2023)
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
Scaling Vision Transformers to 22 Billion Parameters. ICML (2023)
Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR (2023)
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
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR (2023)
Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
Image Captioners Are Scalable Vision Learners Too. CoRR (2023)
Michael Tschannen, Basil Mustafa, Neil Houlsby
CLIPPO: Image-and-Language Understanding from Pixels Only. CVPR (2023)
Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Neil Houlsby
From Sparse to Soft Mixtures of Experts. CoRR (2023)
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
Robust and Efficient Medical Imaging with Self-Supervision. CoRR (2022)
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
Simple Open-Vocabulary Object Detection with Vision Transformers. CoRR (2022)
Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints. CoRR (2022)
Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, Donald Metzler
Unifying Language Learning Paradigms. CoRR (2022)
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
Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 2022 (2022)
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
Simple Open-Vocabulary Object Detection. ECCV (10) (2022)
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
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23 (2022)
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. NeurIPS (2022)
Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. CoRR (2022)
Mathilde Caron, Neil Houlsby, Cordelia Schmid
Location-Aware Self-Supervised Transformers. CoRR (2022)
Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin D. Cubuk
On the surprising tradeoff between ImageNet accuracy and perceptual similarity. CoRR (2022)
Michael Tschannen, Basil Mustafa, Neil Houlsby
Image-and-Language Understanding from Pixels Only. CoRR (2022)
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 Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR (2022)
Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. NeurIPS (2022)
Cédric Renggli, André Susano Pinto, Neil Houlsby, Basil Mustafa, Joan Puigcerver, Carlos Riquelme
Learning to Merge Tokens in Vision Transformers. CoRR (2022)
Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin Dogus Cubuk
Do better ImageNet classifiers assess perceptual similarity better? Trans. Mach. Learn. Res. 2022 (2022)
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
Transcending Scaling Laws with 0.1% Extra Compute. CoRR (2022)
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. CoRR (2022)
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
Scaling Vision Transformers. CVPR (2022)
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
Scaling Vision with Sparse Mixture of Experts. NeurIPS (2021)
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
Revisiting the Calibration of Modern Neural Networks. NeurIPS (2021)
Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby
Scalable Transfer Learning with Expert Models. ICLR (2021)
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
Scaling Vision Transformers. CoRR (2021)
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
MLP-Mixer: An all-MLP Architecture for Vision. NeurIPS (2021)
Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
Representation learning from videos in-the-wild: An object-centric approach. WACV (2021)
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. CoRR (2021)
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR (2021)
Hugo Jair Escalante, Quanming Yao, Wei-Wei Tu, Nelishia Pillay, Rong Qu, Yang Yu, Neil Houlsby
Guest Editorial: Automated Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43 (9) (2021)
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. NeurIPS Datasets and Benchmarks (2021)
Mostafa Dehghani, Yi Tay, Alexey A. Gritsenko, Zhe Zhao, Neil Houlsby, Fernando Diaz, Donald Metzler, Oriol Vinyals
The Benchmark Lottery. CoRR (2021)
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
Revisiting the Calibration of Modern Neural Networks. CoRR (2021)
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
Supervised Transfer Learning at Scale for Medical Imaging. CoRR (2021)
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ICLR (2021)
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
On Robustness and Transferability of Convolutional Neural Networks. CVPR (2021)
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
MLP-Mixer: An all-MLP Architecture for Vision. CoRR (2021)
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
Scaling Vision with Sparse Mixture of Experts. CoRR (2021)
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
Sparse MoEs meet Efficient Ensembles. CoRR (2021)
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
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR (2020)
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
Training general representations for remote sensing using in-domain knowledge. CoRR (2020)
Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby
Scalable Transfer Learning with Expert Models. CoRR (2020)
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
On Robustness and Transferability of Convolutional Neural Networks. CoRR (2020)
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
Training General Representations for Remote Sensing Using in-Domain Knowledge. IGARSS (2020)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
Big Transfer (BiT): General Visual Representation Learning. ECCV (5) (2020)
Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
Automatic Shortcut Removal for Self-Supervised Representation Learning. CoRR (2020)
Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
Representation learning from videos in-the-wild: An object-centric approach. CoRR (2020)
Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
Automatic Shortcut Removal for Self-Supervised Representation Learning. ICML (2020)
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. CoRR (2020)
Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto, Daniel Keysers, Neil Houlsby
Deep Ensembles for Low-Data Transfer Learning. CoRR (2020)
Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
Self-Supervised Learning of Video-Induced Visual Invariances. CVPR (2020)
Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly
On Self Modulation for Generative Adversarial Networks. ICLR (Poster) (2019)
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
In-domain representation learning for remote sensing. CoRR (2019)
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
The Visual Task Adaptation Benchmark. CoRR (2019)
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly
Parameter-Efficient Transfer Learning for NLP. CoRR (2019)
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly
Parameter-Efficient Transfer Learning for NLP. ICML (2019)
Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
Self-Supervised GANs via Auxiliary Rotation Loss. CVPR (2019)
Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
Self-Supervised Learning of Video-Induced Visual Invariances. CoRR (2019)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
Large Scale Learning of General Visual Representations for Transfer. CoRR (2019)
Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo
Transfer Automatic Machine Learning. CoRR (2018)
Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang
Analyzing Language Learned by an Active Question Answering Agent. CoRR (2018)
Ting Chen, Xiaohua Zhai, Neil Houlsby
Self-Supervised GAN to Counter Forgetting. CoRR (2018)
Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly
On Self Modulation for Generative Adversarial Networks. CoRR (2018)
Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang
Ask the Right Questions: Active Question Reformulation with Reinforcement Learning. ICLR (2018)
Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo
Transfer Learning with Neural AutoML. NeurIPS (2018)
Quentin de Laroussilhe, Stanislaw Jastrzebski, Neil Houlsby, Andrea Gesmundo
Neural Architecture Search Over a Graph Search Space. CoRR (2018)
Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
Self-Supervised Generative Adversarial Networks. CoRR (2018)
Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Andrea Gesmundo, Neil Houlsby, Wojciech Gajewski, Wei Wang
Ask the Right Questions: Active Question Reformulation with Reinforcement Learning. CoRR (2017)
José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani
Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. ICML (2014)
Neil Houlsby, Massimiliano Ciaramita
A Scalable Gibbs Sampler for Probabilistic Entity Linking. ECIR (2014)
José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani
Probabilistic Matrix Factorization with Non-random Missing Data. ICML (2014)
Neil Houlsby, David M. Blei
A Filtering Approach to Stochastic Variational Inference. NIPS (2014)
Neil Houlsby, José Miguel Hernández-Lobato, Zoubin Ghahramani
Cold-start Active Learning with Robust Ordinal Matrix Factorization. ICML (2014)
Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani
Active Learning for Interactive Visualization. AISTATS (2013)
Neil Houlsby, Massimiliano Ciaramita
Scalable Probabilistic Entity-Topic Modeling. CoRR (2013)
Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani
Collaborative Gaussian Processes for Preference Learning. NIPS (2012)
Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel
Bayesian Active Learning for Classification and Preference Learning CoRR (2011)