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Journal Articles
- 2024
[j6]Kaiyang Zhou, Ziwei Liu, Xiaohua Zhai, Chunyuan Li, Kate Saenko:
Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models. Int. J. Comput. Vis. 132(4): 1009-1011 (2024)- 2022
- [j5]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) - [j4]Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer:
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. Trans. Mach. Learn. Res. 2022 (2022) - 2016
- [j3]Yuxin Peng, Xiaohua Zhai, Yunzhen Zhao, Xin Huang:
Semi-Supervised Cross-Media Feature Learning With Unified Patch Graph Regularization. IEEE Trans. Circuits Syst. Video Technol. 26(3): 583-596 (2016) - 2014
- [j2]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
Learning Cross-Media Joint Representation With Sparse and Semisupervised Regularization. IEEE Trans. Circuits Syst. Video Technol. 24(6): 965-978 (2014) - 2013
- [j1]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
Cross-media retrieval by intra-media and inter-media correlation mining. Multim. Syst. 19(5): 395-406 (2013)
Conference and Workshop Papers
- 2024
- [c38]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 - [c37]Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai:
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning? ICLR 2024 - 2023
- [c36]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CVPR 2023: 14496-14506 - [c35]Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer:
Sigmoid Loss for Language Image Pre-Training. ICCV 2023: 11941-11952 - [c34]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 - [c33]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning Computer Vision Models With Task Rewards. ICML 2023: 33229-33239 - [c32]Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. NeurIPS 2023 - [c31]Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou:
Three Towers: Flexible Contrastive Learning with Pretrained Image Models. NeurIPS 2023 - [c30]Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer:
Image Captioners Are Scalable Vision Learners Too. NeurIPS 2023 - 2022
- [c29]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CVPR 2022: 1204-1213 - [c28]Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov:
Knowledge distillation: A good teacher is patient and consistent. CVPR 2022: 10915-10924 - [c27]Xiaohua Zhai, Xiao Wang
, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer:
LiT: Zero-Shot Transfer with Locked-image text Tuning. CVPR 2022: 18102-18112 - [c26]Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou:
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation. ECCV (10) 2022: 711-727 - [c25]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 - [c24]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 - [c23]Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. NeurIPS 2022 - 2021
- [c22]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 - [c21]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 - [c20]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 - [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 - 2020
- [c17]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 - [c16]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
Training General Representations for Remote Sensing Using in-Domain Knowledge. IGARSS 2020: 6730-6733 - 2019
- [c15]Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer:
Revisiting Self-Supervised Visual Representation Learning. CVPR 2019: 1920-1929 - [c14]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised GANs via Auxiliary Rotation Loss. CVPR 2019: 12154-12163 - [c13]Lucas Beyer, Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov:
S4L: Self-Supervised Semi-Supervised Learning. ICCV 2019: 1476-1485 - [c12]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
A Large-Scale Study on Regularization and Normalization in GANs. ICML 2019: 3581-3590 - [c11]Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly:
High-Fidelity Image Generation With Fewer Labels. ICML 2019: 4183-4192 - 2013
- [c10]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
Heterogeneous Metric Learning with Joint Graph Regularization for Cross-Media Retrieval. AAAI 2013: 1198-1204 - [c9]Ding Ma, Xiaohua Zhai, Yuxin Peng:
Cross-media retrieval by cluster-based correlation analysis. ICIP 2013: 3986-3990 - [c8]Yuxin Peng, Xiaohua Zhai, Jian Zhang, Lei Huang, Nianzu Li, Panpan Tang, Xin Huang, Yunzhen Zhao:
PKU_ICST at TRECVID2013 : Instance Search Task. TRECVID 2013 - 2012
- [c7]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
Cross-modality correlation propagation for cross-media retrieval. ICASSP 2012: 2337-2340 - [c6]Li Ling, Xiaohua Zhai, Yuxin Peng:
Tri-space and ranking based heterogeneous similarity measure for cross-media retrieval. ICPR 2012: 230-233 - [c5]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
PDSS: patch-descriptor-similarity space for effective face verification. ACM Multimedia 2012: 961-964 - [c4]Xiaohua Zhai, Yuxin Peng, Jianguo Xiao:
Effective Heterogeneous Similarity Measure with Nearest Neighbors for Cross-Media Retrieval. MMM 2012: 312-322 - [c3]Yuxin Peng, Yunbo Peng, Xiaohua Zhai, Jian Zhang, Tianjun Xiao, Xin Huang, Kang Cai:
PKU-ICST @TRECVID2012: Known-item Search Task. TRECVID 2012 - 2009
- [c2]Yuxin Peng, Zhiguo Yang, Lei Cao, Jian Yi, Ning Wan, Yuan Feng, Xiaohua Zhai, En Shi, Hao Li:
PKU-ICST at TRECVID2009: High Level Feature Extraction and Search. TRECVID 2009 - 2006
- [c1]Wei Sun, Yaonan Wang, Xiaohua Zhai:
Adaptive Control Based on Recurrent Fuzzy Wavelet Neural Network and Its Application on Robotic Tracking Control. ISNN (2) 2006: 1166-1171
Informal and Other Publications
- 2024
- [i45]Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai:
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning? CoRR abs/2403.04547 (2024) - [i44]Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai:
LocCa: Visual Pretraining with Location-aware Captioners. CoRR abs/2403.19596 (2024) - [i43]Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Peter Steiner, Xiaohua Zhai, Ibrahim Alabdulmohsin:
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. CoRR abs/2405.13777 (2024) - [i42]Yue Fan, Yongqin Xian, Xiaohua Zhai, Alexander Kolesnikov, Muhammad Ferjad Naeem, Bernt Schiele, Federico Tombari:
Toward a Diffusion-Based Generalist for Dense Vision Tasks. CoRR abs/2407.00503 (2024) - [i41]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
- [i40]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) - [i39]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning computer vision models with task rewards. CoRR abs/2302.08242 (2023) - [i38]Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer:
Sigmoid Loss for Language Image Pre-Training. CoRR abs/2303.15343 (2023) - [i37]Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, André Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai:
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision. CoRR abs/2303.17376 (2023) - [i36]Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. CoRR abs/2305.13035 (2023) - [i35]Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou:
Three Towers: Flexible Contrastive Learning with Pretrained Image Models. CoRR abs/2305.16999 (2023) - [i34]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) - [i33]Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer:
Image Captioners Are Scalable Vision Learners Too. CoRR abs/2306.07915 (2023) - [i32]Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut:
PaLI-3 Vision Language Models: Smaller, Faster, Stronger. CoRR abs/2310.09199 (2023) - [i31]Muhammad Ferjad Naeem, Yongqin Xian, Xiaohua Zhai, Lukas Hoyer, Luc Van Gool, Federico Tombari:
SILC: Improving Vision Language Pretraining with Self-Distillation. CoRR abs/2310.13355 (2023) - 2022
- [i30]Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov:
Better plain ViT baselines for ImageNet-1k. CoRR abs/2205.01580 (2022) - [i29]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) - [i28]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) - [i27]Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. CoRR abs/2209.06640 (2022) - [i26]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) - [i25]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CoRR abs/2212.08013 (2022) - 2021
- [i24]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) - [i23]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) - [i22]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) - [i21]Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer:
Scaling Vision Transformers. CoRR abs/2106.04560 (2021) - [i20]Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov:
Knowledge distillation: A good teacher is patient and consistent. CoRR abs/2106.05237 (2021) - [i19]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) - [i18]Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer:
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. CoRR abs/2106.10270 (2021) - [i17]Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer:
LiT: Zero-Shot Transfer with Locked-image Text Tuning. CoRR abs/2111.07991 (2021) - [i16]Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou:
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation. CoRR abs/2112.09747 (2021) - 2020
- [i15]Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord:
Are we done with ImageNet? CoRR abs/2006.07159 (2020) - [i14]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) - [i13]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
Training general representations for remote sensing using in-domain knowledge. CoRR abs/2010.00332 (2020) - [i12]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) - [i11]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) - 2019
- [i10]Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer:
Revisiting Self-Supervised Visual Representation Learning. CoRR abs/1901.09005 (2019) - [i9]Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly:
High-Fidelity Image Generation With Fewer Labels. CoRR abs/1903.02271 (2019) - [i8]Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer:
S4L: Self-Supervised Semi-Supervised Learning. CoRR abs/1905.03670 (2019) - [i7]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) - [i6]Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby:
In-domain representation learning for remote sensing. CoRR abs/1911.06721 (2019) - [i5]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
- [i4]Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai:
MemGEN: Memory is All You Need. CoRR abs/1803.11203 (2018) - [i3]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
The GAN Landscape: Losses, Architectures, Regularization, and Normalization. CoRR abs/1807.04720 (2018) - [i2]Ting Chen, Xiaohua Zhai, Neil Houlsby:
Self-Supervised GAN to Counter Forgetting. CoRR abs/1810.11598 (2018) - [i1]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised Generative Adversarial Networks. CoRR abs/1811.11212 (2018)
Coauthor Index
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, and 
to record detail pages.
load references from crossref.org and opencitations.net
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
.
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last updated on 2024-10-08 21:26 CEST by the dblp team
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