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PreDiff: Precipitation Nowcasting with Latent Diffusion Models.
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Maddix Robinson, Yi Zhu, Mu Li, Yuyang Bernie Wang.
Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS), 2023.
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Towards Geospatial Foundation Models via Continual Pretraining.
Matias Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen.
International Conference on Computer Vision (ICCV), 2023.
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Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation.
Yuxin Ren*, Zihan Zhong*, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li (* indicates equal contribution)
The 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023.
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XTab: Cross-table Pretraining for Tabular Transformers.
Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran
Fortieth International Conference on Machine Learning (ICML), 2023.
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LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation.
Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li
The AI for Content Creation (AI4CC) workshop at CVPR, 2023.
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Parameter-Efficient Fine-Tuning Design Spaces.
Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang
The Eleventh International Conference on Learning Representations (ICLR), 2023.
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Learning Multimodal Data Augmentation in Feature Space.
Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson
The Eleventh International Conference on Learning Representations (ICLR), 2023.
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Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.
Zhihan Gao, Xingjian Shi*, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung (* Contact person)
Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
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Benchmarking Multimodal AutoML for Tabular Data with Text Fields.
Xingjian Shi*, Jonas Mueller*, Nick Erickson, Mu Li, Alexander J. Smola (* indicates equal contribution)
Proceedings of the Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, 2021.
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Symbolic Music Generation with Transformer-GANs.
Aashiq Muhamed*, Liang Li*, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola (* indicates equal contribution)
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021.
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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu
Journal of Machine Learning Research (JMLR), 2020.
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STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems.
Jiani Zhang, Xingjian Shi, Shenglin Zhao, Irwin King
Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 2019.
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GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs.
Xingjian Shi*, Jiani Zhang*, Junyuan Xie, Hao Ma, Irwin King, Dit-Yan Yeung (* indicates equal contribution)
Thirty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI), 2018.
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Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model.
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong, Wang-chun Woo
Thirty-First Annual Conference on Neural Information Processing Systems (NeurIPS), 2017. (Accepted as Spotlight)
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Spatiotemporal Modeling for Crowd Counting in Videos.
Feng Xiong, Xingjian Shi, Dit-Yan Yeung
Sixteenth IEEE International Conference on Computer Vision (ICCV), 2017.
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Dynamic Key-Value Memory Networks for Knowledge Tracing.
Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung
Twenty-Sixth International Conference on World Wide Web (WWW), 2017.
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Relational Deep Learning: A Deep Latent Variable Model for Link Prediction.
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017.
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Natural Parameter Networks: A Class of Probabilistic Neural Networks.
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Thirtieth Annual Conference on Neural Information Processing Systems (NeurIPS), 2016.
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Collaborative Recurrent Autoencoder: Recommend While Learning to Fill in the Blanks.
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Thirtieth Annual Conference on Neural Information Processing Systems (NeurIPS), 2016.
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Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong, Wang-chun Woo
Twenty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2015.
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Relational Stacked Denoising Autoencoder for Tag Recommendation.
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), 2015.
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Distributed Stochastic ADMM for Matrix Factorization.
Zhi-Qin Yu, Xingjian Shi, Ling Yan, Wu-Jun Li
Twenty-Third ACM International Conference on Information and Knowledge Management (CIKM), 2014.