Chen Wang

I am an Assistant Professor at the Computer Science and Engineering (CSE), University at Buffalo (UB).

At the intersection of perception, spatial reasoning, and decision-making, we are committed to advancing mobile robots toward human-level autonomy by developing algorithms and systems that can efficiently and robustly:

Perceive and interpret various sensory inputs such as images, point clouds, and proprioceptive data.
Integrate neural and symbolic memory representations to capture spatial common sense and semantic knowledge.
Reason, plan, and act in real time to navigate in, interact with, and adapt within unstructured and dynamic environments.

A central paradigm we advocate is imperative learning (IL), a unified neuro-symbolic learning framework for robot autonomy that promotes data-efficient learning through structured reasoning. IL is inherently self-supervised, modular, and end-to-end learnable with symbolic reasoning grounded in physical laws and logical rules.

We are also leading the development of PyPose, an open-source library for differentiable robotics on manifolds. Notably, PyPose has accumulated over 160,000 downloads in 2025, according to PyPi Stats.

Experience & Education

Assistant Professor, University at Buffalo (UB), USA, 2022 - Present
Postdoctoral Fellow, Robotics Institute, Carnegie Mellon University, USA, 2019 - 2022
Ph.D., Nanyang Technological University (NTU), Singapore, 2014 - 2019
Bachelor, Beijing Institute of Technology (BIT), China, 2010 - 2014

Awards

UB CSE Excellence in Research Award, 2024
Sony Research Award, 2024
Cisco Research Award, 2023

Services

Associate Editor for Top Journals
- IEEE Transactions on Robotics (T-RO), Jan. 2026 - Present
- International Journal of Robotics Research (IJRR), Jan. 2023 - Present
- IEEE Robotics and Automation Letters (RA-L), Aug. 2021 - Aug 2024
Area Chair for Top Conferences
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 - Present
- Conference on Neural Information Processing Systems (NeurIPS), 2024 - Present
- IEEE International Conference on Robotics and Automation (ICRA), 2025 - Present
Leading Guest Editor for IJRR Special Issue on Foundation Models and Neuro-Symbolic AI for Robotics
Associate Co-chair for IEEE RAS Technical Committee for Computer & Robot Vision, Dec. 2022 - Present

Information

Selected Publications

Selected publications highlighting key contributions in neuro-symbolic robot autonomy, including framework development, system design, and foundations in learning and representation. Full publication list is here.

Representative Works

Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy.
Chen Wang, Kaiyi Ji, Junyi Geng, Zhongqiang Ren, Taimeng Fu, Fan Yang, Yifan Guo, Haonan He, Xiangyu Chen, Zitong Zhan, Qiwei Du, Shaoshu Su, Bowen Li, Yuheng Qiu, Yi Du, Qihang Li, Yifan Yang, Xiao Lin, Zhipeng Zhao.
International Journal of Robotics Research (IJRR), 2025.

Unifying robot autonomy via neuro-symbolic learning
```
@article{wang2025imperative,
  title = {Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy},
  author = {Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng},
  journal = {International Journal of Robotics Research (IJRR)},
  year = {2025},
  url = {https://arxiv.org/abs/2406.16087},
  code = {https://github.com/sair-lab/iSeries},
  website = {https://sairlab.org/iseries},
  cover = {/img/posts/2024-07-02-iSeries/il-cover.jpg},
  addendum = {Unifying robot autonomy via neuro-symbolic learning}
}
```
```
Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng, "Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy," International Journal of Robotics Research (IJRR), 2025.
```
Resilient Odometry via Hierarchical Adaptation.
Shibo Zhao, Sifan Zhou, Yuchen Zhang, Ji Zhang, Chen Wang, Wenshan Wang, Sebastian Scherer.
Science Robotics, vol. 10, no. 109, 2025.

Top featured article in Science Robotics; Imperative learning enables all-weather resiliency; Exhibiting only 0.000067 (0.2m / 3km) drift without loop closure
```
@article{zhao2025resilient,
  title = {Resilient Odometry via Hierarchical Adaptation},
  author = {Zhao, Shibo and Zhou, Sifan and Zhang, Yuchen and Zhang, Ji and Wang, Chen and Wang, Wenshan and Scherer, Sebastian},
  journal = {Science Robotics},
  volume = {10},
  number = {109},
  year = {2025},
  publisher = {American Association for the Advancement of Science},
  url = {https://doi.org/10.1126/scirobotics.adv1818},
  website = {https://superodometry.com/},
  code = {https://github.com/superxslam/SuperOdom},
  cover = {/img/pubs/SuperOdometry.mp4},
  addendum = {Top featured article in Science Robotics; Imperative learning enables all-weather resiliency; Exhibiting only 0.000067 (0.2m / 3km) drift without loop closure}
}
```
```
Zhao, Shibo and Zhou, Sifan and Zhang, Yuchen and Zhang, Ji and Wang, Chen and Wang, Wenshan and Scherer, Sebastian, "Resilient Odometry via Hierarchical Adaptation," Science Robotics, 2025.
```
PyPose: A Library for Robot Learning with Physics-based Optimization.
Chen Wang, Dasong Gao, Kuan Xu, Junyi Geng, Yaoyu Hu, Yuheng Qiu, Bowen Li, Fan Yang, Brady Moon, Abhinav Pandey, Aryan, Jiahe Xu, Tianhao Wu, Haonan He, Daning Huang, Zhongqiang Ren, Shibo Zhao, Taimeng Fu, Pranay Reddy, Xiao Lin, Wenshan Wang, Jingnan Shi, Rajat Talak, Kun Cao, Yi Du, Han Wang, Huai Yu, Shanzhao Wang, Siyu Chen, Ananth Kashyap, Rohan Bandaru, Karthik Dantu, Jiajun Wu, Lihua Xie, Luca Carlone, Marco Hutter, Sebastian Scherer.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22024–22034, 2023.

Python library accumulated over 160,000 downloads in 2025
```
@inproceedings{wang2023pypose,
  title = {{PyPose}: A Library for Robot Learning with Physics-based Optimization},
  author = {Wang, Chen and Gao, Dasong and Xu, Kuan and Geng, Junyi and Hu, Yaoyu and Qiu, Yuheng and Li, Bowen and Yang, Fan and Moon, Brady and Pandey, Abhinav and Aryan and Xu, Jiahe and Wu, Tianhao and He, Haonan and Huang, Daning and Ren, Zhongqiang and Zhao, Shibo and Fu, Taimeng and Reddy, Pranay and Lin, Xiao and Wang, Wenshan and Shi, Jingnan and Talak, Rajat and Cao, Kun and Du, Yi and Wang, Han and Yu, Huai and Wang, Shanzhao and Chen, Siyu and Kashyap, Ananth and Bandaru, Rohan and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Carlone, Luca and Hutter, Marco and Scherer, Sebastian},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  pages = {22024--22034},
  url = {https://arxiv.org/abs/2209.15428},
  code = {https://github.com/pypose/pypose},
  video = {https://youtu.be/XDtUDIWuGng},
  website = {https://sairlab.org/pypose/},
  cover = {/img/posts/pypose/robots.jpg},
  addendum = {Python library accumulated over 160,000 downloads in 2025}
}
```
```
Wang, Chen and Gao, Dasong and Xu, Kuan and Geng, Junyi and Hu, Yaoyu and Qiu, Yuheng and Li, Bowen and Yang, Fan and Moon, Brady and Pandey, Abhinav and Aryan and Xu, Jiahe and Wu, Tianhao and He, Haonan and Huang, Daning and Ren, Zhongqiang and Zhao, Shibo and Fu, Taimeng and Reddy, Pranay and Lin, Xiao and Wang, Wenshan and Shi, Jingnan and Talak, Rajat and Cao, Kun and Du, Yi and Wang, Han and Yu, Huai and Wang, Shanzhao and Chen, Siyu and Kashyap, Ananth and Bandaru, Rohan and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Carlone, Luca and Hutter, Marco and Scherer, Sebastian, "PyPose: A Library for Robot Learning with Physics-based Optimization," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
```

Neuro-Symbolic Robot Autonomy

Fast Task Planning with Neuro-Symbolic Relaxation.
Qiwei Du, Bowen Li, Yi Du, Shaoshu Su, Taimeng Fu, Zitong Zhan, Zhipeng Zhao, Chen Wang.
IEEE Robotics and Automation Letters (RA-L), vol. 11, no. 3, pp. 3684–3691, 2026.

An elegant real-world demonstration of interactive navigation
```
@article{du2026fast,
  title = {Fast Task Planning with Neuro-Symbolic Relaxation},
  author = {Du, Qiwei and Li, Bowen and Du, Yi and Su, Shaoshu and Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Wang, Chen},
  journal = {IEEE Robotics and Automation Letters (RA-L)},
  year = {2026},
  volume = {11},
  number = {3},
  pages = {3684-3691},
  url = {https://arxiv.org/abs/2507.15975},
  website = {https://sairlab.org/flax/},
  code = {https://github.com/sair-lab/flax},
  video = {https://youtu.be/_4DYcqwycnQ},
  cover = {/img/posts/2025-07-21-flax/Flax.mp4},
  addendum = {An elegant real-world demonstration of interactive navigation}
}
```
```
Du, Qiwei and Li, Bowen and Du, Yi and Su, Shaoshu and Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Wang, Chen, "Fast Task Planning with Neuro-Symbolic Relaxation," IEEE Robotics and Automation Letters (RA-L), 2026.
```
iWalker: Imperative Visual Planning for Walking Humanoid Robot.
Xiao Lin, Yuhao Huang, Taimeng Fu, Xiaobin Xiong, Chen Wang.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2865–2872, 2025.

Best Workshop Paper Award; Enabling humanoid walking via self-supervised footstep planning
```
@inproceedings{lin2025iwalker,
  title = {{iWalker}: Imperative Visual Planning for Walking Humanoid Robot},
  author = {Lin, Xiao and Huang, Yuhao and Fu, Taimeng and Xiong, Xiaobin and Wang, Chen},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {2865--2872},
  year = {2025},
  url = {https://arxiv.org/abs/2409.18361},
  video = {https://youtu.be/FPV74PznzTU},
  website = {https://sairlab.org/iwalker},
  cover = {/img/posts/2024-09-30-iwalker/thumbnail.gif},
  addendum = {Best Workshop Paper Award; Enabling humanoid walking via self-supervised footstep planning}
}
```
```
Lin, Xiao and Huang, Yuhao and Fu, Taimeng and Xiong, Xiaobin and Wang, Chen, "iWalker: Imperative Visual Planning for Walking Humanoid Robot," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
```
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving.
Zhipeng Zhao, Bowen Li, Yi Du, Taimeng Fu, Chen Wang.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 11670–11677, 2024.

Neuro-symbolic learning pushes SOTA by 46% higher accuracy using 3% model size
```
@inproceedings{zhao2024physord,
  title = {{PhysORD}: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving},
  author = {Zhao, Zhipeng and Li, Bowen and Du, Yi and Fu, Taimeng and Wang, Chen},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = {2024},
  pages = {11670--11677},
  url = {https://arxiv.org/abs/2404.01596},
  code = {https://github.com/sair-lab/PhysORD},
  video = {https://youtu.be/kYa9dAyUkYI},
  website = {https://sairlab.org/physord},
  cover = {/img/posts/2024-08-17-physord/physord_exp.gif},
  addendum = {Neuro-symbolic learning pushes SOTA by 46\% higher accuracy using 3\% model size}
}
```
```
Zhao, Zhipeng and Li, Bowen and Du, Yi and Fu, Taimeng and Wang, Chen, "PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.
```
iPlanner: Imperative Path Planning.
Fan Yang, Chen Wang, Cesar Cadena, Marco Hutter.
Robotics: Science and Systems (RSS), 2023.

A pioneer work in visual planning using imperative learning
```
@inproceedings{yang2023iplanner,
  author = {Yang, Fan and Wang, Chen and Cadena, Cesar and Hutter, Marco},
  title = {{iPlanner}: Imperative Path Planning},
  booktitle = {Robotics: Science and Systems (RSS)},
  url = {https://arxiv.org/abs/2302.11434},
  code = {https://github.com/sair-lab/iPlanner},
  year = {2023},
  website = {https://sairlab.org/iPlanner/},
  cover = {/img/posts/2023-07-30-iPlanner/iplanner-cover.gif},
  addendum = {A pioneer work in visual planning using imperative learning}
}
```
```
Yang, Fan and Wang, Chen and Cadena, Cesar and Hutter, Marco, "iPlanner: Imperative Path Planning," Robotics: Science and Systems (RSS), 2023.
```

Adaptive Learning for Robotic Systems

Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning.
Fan Yang, Per Frivik, David Hoeller, Chen Wang, Cesar Cadena, Marco Hutter.
International Journal of Robotics Research (IJRR), 2025.
```
@article{yang2025improving,
  title = {Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning},
  author = {Yang, Fan and Frivik, Per and Hoeller, David and Wang, Chen and Cadena, Cesar and Hutter, Marco},
  journal = {International Journal of Robotics Research (IJRR)},
  year = {2025},
  url = {https://arxiv.org/abs/2506.05997},
  code = {https://github.com/leggedrobotics/sru-pytorch-spatial-learning},
  website = {https://michaelfyang.github.io/sru-project-website/},
  cover = {/img/pubs/SRU.mp4}
}
```
```
Yang, Fan and Frivik, Per and Hoeller, David and Wang, Chen and Cadena, Cesar and Hutter, Marco, "Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning," International Journal of Robotics Research (IJRR), 2025.
```
AirSLAM: An Efficient and Illumination-Robust Point-Line Visual SLAM System.
Kuan Xu, Yuefan Hao, Shenghai Yuan, Chen Wang, Lihua Xie.
IEEE Transactions on Robotics (T-RO), vol. 41, pp. 1673–1692, 2025.

Real-time visual SLAM at 70Hz with superior accuracy
```
@article{xu2025airslam,
  title = {{AirSLAM}: An Efficient and Illumination-Robust Point-Line Visual SLAM System},
  author = {Xu, Kuan and Hao, Yuefan and Yuan, Shenghai and Wang, Chen and Xie, Lihua},
  journal = {IEEE Transactions on Robotics (T-RO)},
  year = {2025},
  volume = {41},
  pages = {1673-1692},
  url = {https://arxiv.org/abs/2408.03520},
  code = {https://github.com/sair-lab/AirSLAM},
  video = {https://youtu.be/5OcR5KeO5nc},
  website = {https://sairlab.org/airslam},
  cover = {/img/posts/2024-08-15-airslam/AirSLAM.mp4},
  addendum = {Real-time visual SLAM at 70Hz with superior accuracy}
}
```
```
Xu, Kuan and Hao, Yuefan and Yuan, Shenghai and Wang, Chen and Xie, Lihua, "AirSLAM: An Efficient and Illumination-Robust Point-Line Visual SLAM System," IEEE Transactions on Robotics (T-RO), 2025.
```
Unsupervised Online Learning for Robotic Interestingness with Visual Memory.
Chen Wang, Wenshan Wang, Yuheng Qiu, Yafei Hu, Seungchan Kim, Sebastian Scherer.
IEEE Transactions on Robotics (T-RO), vol. 38, no. 4, pp. 2446–2461, 2021.
```
@article{wang2021unsupervised,
  title = {Unsupervised Online Learning for Robotic Interestingness with Visual Memory},
  author = {Wang, Chen and Wang, Wenshan and Qiu, Yuheng and Hu, Yafei and Kim, Seungchan and Scherer, Sebastian},
  journal = {IEEE Transactions on Robotics (T-RO)},
  year = {2021},
  volume = {38},
  number = {4},
  pages = {2446--2461},
  url = {https://arxiv.org/abs/2111.09793},
  code = {https://github.com/sair-lab/interestingness},
  website = {https://sairlab.org/interestingness/},
  cover = {/img/posts/2020-05-01-interestingness/interestingness-tro.jpg}
}
```
```
Wang, Chen and Wang, Wenshan and Qiu, Yuheng and Hu, Yafei and Kim, Seungchan and Scherer, Sebastian, "Unsupervised Online Learning for Robotic Interestingness with Visual Memory," IEEE Transactions on Robotics (T-RO), 2021.
```

Foundations in Learning and Representation

SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization.
Yi Du, Zhipeng Zhao, Shaoshu Su, Sharath Golluri, Haoze Zheng, Runmao Yao, Chen Wang.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16953–16964, 2025.

Unifying point cloud processing via a single diffusion model
```
@inproceedings{du2025superpc,
  title = {{SuperPC}: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization},
  author = {Du, Yi and Zhao, Zhipeng and Su, Shaoshu and Golluri, Sharath and Zheng, Haoze and Yao, Runmao and Wang, Chen},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  url = {https://arxiv.org/abs/2503.14558},
  year = {2025},
  pages = {16953--16964},
  code = {https://github.com/sair-lab/superpc},
  website = {https://sairlab.org/superpc/},
  cover = {/img/posts/2025-02-28-superpc/superpc_cover.mp4},
  addendum = {Unifying point cloud processing via a single diffusion model}
}
```
```
Du, Yi and Zhao, Zhipeng and Su, Shaoshu and Golluri, Sharath and Zheng, Haoze and Yao, Runmao and Wang, Chen, "SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
```
iMatching: Imperative Correspondence Learning.
Zitong Zhan, Dasong Gao, Yun-Jou Lin, Youjie Xia, Chen Wang.
European Conference on Computer Vision (ECCV), pp. 183–200, 2024.

A self-supervised feature learning approach pushes SOTA by 30% accuracy gain
```
@inproceedings{zhan2024imatching,
  title = {{iMatching}: Imperative Correspondence Learning},
  author = {Zhan, Zitong and Gao, Dasong and Lin, Yun-Jou and Xia, Youjie and Wang, Chen},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year = {2024},
  pages = {183--200},
  url = {https://arxiv.org/abs/2312.02141},
  code = {https://github.com/sair-lab/iMatching},
  website = {https://sairlab.org/iMatching},
  cover = {/img/posts/2024-07-03-imatching/imatching.gif},
  addendum = {A self-supervised feature learning approach pushes SOTA by 30\% accuracy gain}
}
```
```
Zhan, Zitong and Gao, Dasong and Lin, Yun-Jou and Xia, Youjie and Wang, Chen, "iMatching: Imperative Correspondence Learning," European Conference on Computer Vision (ECCV), 2024.
```
Lifelong Graph Learning.
Chen Wang, Yuheng Qiu, Dasong Gao, Sebastian Scherer.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13719–13728, 2022.

Selected as Oral presentation (4.2%)
```
@inproceedings{wang2022lifelong,
  title = {Lifelong Graph Learning},
  author = {Wang, Chen and Qiu, Yuheng and Gao, Dasong and Scherer, Sebastian},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
  pages = {13719--13728},
  url = {https://arxiv.org/abs/2009.00647},
  code = {https://github.com/sair-lab/LGL},
  video = {https://youtu.be/711oo3Mi2Do},
  website = {https://sairlab.org/lgl/},
  cover = {/img/posts/2022-03-05-lgl/matching.jpg},
  addendum = {Selected as Oral presentation (4.2\%)}
}
```
```
Wang, Chen and Qiu, Yuheng and Gao, Dasong and Scherer, Sebastian, "Lifelong Graph Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
```
Visual Memorability for Robotic Interestingness via Unsupervised Online Learning.
Chen Wang, Wenshan Wang, Yuheng Qiu, Yafei Hu, Sebastian Scherer.
European Conference on Computer Vision (ECCV), pp. 52–68, 2020.

Selected as Oral presentation (2%)
```
@inproceedings{wang2020visual,
  title = {Visual Memorability for Robotic Interestingness via Unsupervised Online Learning},
  author = {Wang, Chen and Wang, Wenshan and Qiu, Yuheng and Hu, Yafei and Scherer, Sebastian},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year = {2020},
  pages = {52--68},
  url = {https://arxiv.org/abs/2005.08829},
  code = {https://github.com/sair-lab/interestingness/tree/eccv},
  video = {https://youtu.be/o9LrDlemerE},
  addendum = {Selected as Oral presentation (2\%)},
  cover = {/img/posts/2020-05-01-interestingness/interestingness_video_short.mp4},
  website = {https://sairlab.org/interestingness/}
}
```
```
Wang, Chen and Wang, Wenshan and Qiu, Yuheng and Hu, Yafei and Scherer, Sebastian, "Visual Memorability for Robotic Interestingness via Unsupervised Online Learning," European Conference on Computer Vision (ECCV), 2020.
```
Kervolutional Neural Networks.
Chen Wang, Jianfei Yang, Lihua Xie, Junsong Yuan.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 31–40, 2019.

Selected as Oral presentation (5.6%)
```
@inproceedings{wang2019kervolutional,
  title = {Kervolutional Neural Networks},
  author = {Wang, Chen and Yang, Jianfei and Xie, Lihua and Yuan, Junsong},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages = {31--40},
  year = {2019},
  url = {https://arxiv.org/abs/1904.03955},
  code = {https://github.com/sair-lab/kervolution},
  cover = {/img/pubs/knn.mp4},
  addendum = {Selected as Oral presentation (5.6\%)}
}
```
```
Wang, Chen and Yang, Jianfei and Xie, Lihua and Yuan, Junsong, "Kervolutional Neural Networks," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
```