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2020 – today
- 2024
[c43]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:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444- [c42]Andreas Bär, Neil Houlsby, Mostafa Dehghani, Manoj Kumar:
Frozen Feature Augmentation for Few-Shot Image Classification. CVPR 2024: 16046-16057 - [c41]Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. ICLR 2024 - [c40]Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Neil Houlsby:
From Sparse to Soft Mixtures of Experts. ICLR 2024 - [c39]Mathilde Caron, Neil Houlsby, Cordelia Schmid:
Location-Aware Self-Supervised Transformers for Semantic Segmentation. WACV 2024: 116-126 - [i58]Andreas Bär, Neil Houlsby, Mostafa Dehghani, Manoj Kumar:
Frozen Feature Augmentation for Few-Shot Image Classification. CoRR abs/2403.10519 (2024) - [i57]Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan:
Capabilities of Gemini Models in Medicine. CoRR abs/2404.18416 (2024) - [i56]Jonathan Roberts, Kai Han, Neil Houlsby, Samuel Albanie:
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation. CoRR abs/2405.08807 (2024) - [i55]Manoj Kumar, Neil Houlsby, Emiel Hoogeboom:
Semantica: An Adaptable Image-Conditioned Diffusion Model. CoRR abs/2405.14857 (2024) - [i54]Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner
, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai:
PaliGemma: A versatile 3B VLM for transfer. CoRR abs/2407.07726 (2024) - 2023
- [j5]Manoj Kumar, Mostafa Dehghani, Neil Houlsby:
Dual PatchNorm. Trans. Mach. Learn. Res. 2023 (2023) - [c38]Michael Tschannen, Basil Mustafa, Neil Houlsby:
CLIPPO: Image-and-Language Understanding from Pixels Only. CVPR 2023: 11006-11017 - [c37]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. EMNLP 2023: 1471-1486 - [c36]Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou:
Massively Scaling Heteroscedastic Classifiers. ICLR 2023 - [c35]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 - [c34]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 - [c33]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: 7480-7512 - [c32]Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You:
Adaptive Computation with Elastic Input Sequence. ICML 2023: 38971-38988 - [c31]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 - [c30]Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby:
Scaling Open-Vocabulary Object Detection. NeurIPS 2023 - [c29]Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer:
Image Captioners Are Scalable Vision Learners Too. NeurIPS 2023 - [i53]Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou:
Massively Scaling Heteroscedastic Classifiers. CoRR abs/2301.12860 (2023) - [i52]Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You:
Adaptive Computation with Elastic Input Sequence. CoRR abs/2301.13195 (2023) - [i51]Manoj Kumar, Mostafa Dehghani, Neil Houlsby:
Dual PatchNorm. CoRR abs/2302.01327 (2023) - [i50]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 Nader 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 abs/2302.05442 (2023) - [i49]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 abs/2305.18565 (2023) - [i48]Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer:
Image Captioners Are Scalable Vision Learners Too. CoRR abs/2306.07915 (2023) - [i47]Matthias Minderer, Alexey A. Gritsenko, Neil Houlsby:
Scaling Open-Vocabulary Object Detection. CoRR abs/2306.09683 (2023) - [i46]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 abs/2307.06304 (2023) - [i45]Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Neil Houlsby:
From Sparse to Soft Mixtures of Experts. CoRR abs/2308.00951 (2023) - [i44]Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. CoRR abs/2309.08520 (2023) - 2022
- [j4]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: 226:1-226:61 (2022) - [j3]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) - [j2]Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin Dogus Cubuk:
Do better ImageNet classifiers assess perceptual similarity better? Trans. Mach. Learn. Res. 2022 (2022) - [c28]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CVPR 2022: 1204-1213 - [c27]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: 728-755 - [c26]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 - [c25]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby:
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. NeurIPS 2022 - [i43]Cédric Renggli, André Susano Pinto, Neil Houlsby, Basil Mustafa, Joan Puigcerver, Carlos Riquelme:
Learning to Merge Tokens in Vision Transformers. CoRR abs/2202.12015 (2022) - [i42]Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin D. Cubuk:
On the surprising tradeoff between ImageNet accuracy and perceptual similarity. CoRR abs/2203.04946 (2022) - [i41]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 abs/2205.05131 (2022) - [i40]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 abs/2205.06230 (2022) - [i39]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 abs/2205.09723 (2022) - [i38]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 abs/2205.10337 (2022) - [i37]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby:
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. CoRR abs/2206.02770 (2022) - [i36]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:
PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR abs/2209.06794 (2022) - [i35]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 abs/2210.11399 (2022) - [i34]Mathilde Caron, Neil Houlsby, Cordelia Schmid:
Location-Aware Self-Supervised Transformers. CoRR abs/2212.02400 (2022) - [i33]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 abs/2212.05055 (2022) - [i32]Michael Tschannen, Basil Mustafa, Neil Houlsby:
Image-and-Language Understanding from Pixels Only. CoRR abs/2212.08045 (2022) - 2021
- [j1]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): 2887-2890 (2021) - [c24]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: 16458-16468 - [c23]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 - [c22]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 - [c21]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 - [c20]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: 8583-8595 - [c19]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: 15682-15694 - [c18]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: 24261-24272 - [c17]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: 177-187 - [i31]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 abs/2101.05913 (2021) - [i30]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 abs/2104.02638 (2021) - [i29]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 abs/2104.04191 (2021) - [i28]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 abs/2105.01601 (2021) - [i27]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CoRR abs/2106.04560 (2021) - [i26]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 abs/2106.05974 (2021) - [i25]Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. CoRR abs/2106.07998 (2021) - [i24]Mostafa Dehghani, Yi Tay, Alexey A. Gritsenko, Zhe Zhao, Neil Houlsby, Fernando Diaz, Donald Metzler, Oriol Vinyals:
The Benchmark Lottery. CoRR abs/2107.07002 (2021) - [i23]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 abs/2110.03360 (2021) - 2020
- [c16]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CVPR 2020: 13803-13812 - [c15]Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby:
Big Transfer (BiT): General Visual Representation Learning. ECCV (5) 2020: 491-507 - [c14]Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen:
Automatic Shortcut Removal for Self-Supervised Representation Learning. ICML 2020: 6927-6937 - [c13]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
Training General Representations for Remote Sensing Using in-Domain Knowledge. IGARSS 2020: 6730-6733 - [i22]Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen:
Automatic Shortcut Removal for Self-Supervised Representation Learning. CoRR abs/2002.08822 (2020) - [i21]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 abs/2007.08558 (2020) - [i20]Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby:
Scalable Transfer Learning with Expert Models. CoRR abs/2009.13239 (2020) - [i19]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
Training general representations for remote sensing using in-domain knowledge. CoRR abs/2010.00332 (2020) - [i18]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 abs/2010.02808 (2020) - [i17]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Deep Ensembles for Low-Data Transfer Learning. CoRR abs/2010.06866 (2020) - [i16]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 abs/2010.11929 (2020) - [i15]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 abs/2011.03395 (2020)
2010 – 2019
- 2019
- [c12]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised GANs via Auxiliary Rotation Loss. CVPR 2019: 12154-12163 - [c11]Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly:
On Self Modulation for Generative Adversarial Networks. ICLR (Poster) 2019 - [c10]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: 2790-2799 - [i14]Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, Sylvain Gelly:
Parameter-Efficient Transfer Learning for NLP. CoRR abs/1902.00751 (2019) - [i13]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 abs/1910.04867 (2019) - [i12]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
In-domain representation learning for remote sensing. CoRR abs/1911.06721 (2019) - [i11]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CoRR abs/1912.02783 (2019) - [i10]Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby:
Large Scale Learning of General Visual Representations for Transfer. CoRR abs/1912.11370 (2019) - 2018
- [c9]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 - [c8]Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo:
Transfer Learning with Neural AutoML. NeurIPS 2018: 8366-8375 - [i9]Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang:
Analyzing Language Learned by an Active Question Answering Agent. CoRR abs/1801.07537 (2018) - [i8]Catherine Wong, Neil Houlsby, Yifeng Lu, Andrea Gesmundo:
Transfer Automatic Machine Learning. CoRR abs/1803.02780 (2018) - [i7]Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly:
On Self Modulation for Generative Adversarial Networks. CoRR abs/1810.01365 (2018) - [i6]Ting Chen, Xiaohua Zhai, Neil Houlsby:
Self-Supervised GAN to Counter Forgetting. CoRR abs/1810.11598 (2018) - [i5]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised Generative Adversarial Networks. CoRR abs/1811.11212 (2018) - [i4]Quentin de Laroussilhe, Stanislaw Jastrzebski, Neil Houlsby, Andrea Gesmundo:
Neural Architecture Search Over a Graph Search Space. CoRR abs/1812.10666 (2018) - 2017
- [i3]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 abs/1705.07830 (2017) - 2014
- [c7]Neil Houlsby, Massimiliano Ciaramita:
A Scalable Gibbs Sampler for Probabilistic Entity Linking. ECIR 2014: 335-346 - [c6]José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani:
Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. ICML 2014: 379-387 - [c5]Neil Houlsby, José Miguel Hernández-Lobato, Zoubin Ghahramani:
Cold-start Active Learning with Robust Ordinal Matrix Factorization. ICML 2014: 766-774 - [c4]José Miguel Hernández-Lobato, Neil Houlsby, Zoubin Ghahramani:
Probabilistic Matrix Factorization with Non-random Missing Data. ICML 2014: 1512-1520 - [c3]Neil Houlsby, David M. Blei:
A Filtering Approach to Stochastic Variational Inference. NIPS 2014: 2114-2122 - 2013
- [c2]Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani:
Active Learning for Interactive Visualization. AISTATS 2013: 342-350 - [i2]Neil Houlsby, Massimiliano Ciaramita:
Scalable Probabilistic Entity-Topic Modeling. CoRR abs/1309.0337 (2013) - 2012
- [c1]Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani:
Collaborative Gaussian Processes for Preference Learning. NIPS 2012: 2105-2113 - 2011
- [i1]Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel:
Bayesian Active Learning for Classification and Preference Learning. CoRR abs/1112.5745 (2011)
Coauthor Index
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