Tian Han

According to our database, Tian Han authored at least 43 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving Adversarial Energy-Based Model via Diffusion Process.

Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Latent Space Hierarchical EBM Diffusion Models.

Jiali Cui, Tian Han

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Layerwise Change of Knowledge in Neural Networks.

Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting.

Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Learning Energy-based Model via Dual-MCMC Teaching.

Jiali Cui, Tian Han

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Hierarchical Features with Joint Latent Space Energy-Based Prior.

Jiali Cui, Ying Nian Wu, Tian Han

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Learning Joint Latent Space EBM Prior Model for Multi-layer Generator.

Jiali Cui, Ying Nian Wu, Tian Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry.

Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model.

Zhisheng Xiao, Tian Han

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning from the Tangram to Solve Mini Visual Tasks.

Yizhou Zhao, Liang Qiu, Pan Lu, Feng Shi, Tian Han, Song-Chun Zhu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs.

Chang Lu, Tian Han, Yue Ning

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Towards multi-scale deep features learning with correlation metric for person re-identification.

Dandan Zhu, Qiangqiang Zhou, Tian Han, Yongqing Chen, Defang Zhao, Xiaokang Yang

Knowl. Based Syst., 2021

GenMotion: Data-driven Motion Generators for Real-time Animation Synthesis.

Yizhou Zhao, Wensi Ai, Liang Qiu, Pan Lu, Feng Shi, Tian Han, Song-Chun Zhu

CoRR, 2021

Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI.

Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang

CoRR, 2021

STAR: Sparse Transformer-based Action Recognition.

Feng Shi, Chonghan Lee, Liang Qiu, Yizhou Zhao, Tianyi Shen, Shivran Muralidhar, Tian Han, Song-Chun Zhu, Vijaykrishnan Narayanan

CoRR, 2021

Lavs: A Lightweight Audio-Visual Saliency Prediction Model.

Dandan Zhu, Defang Zhao, Xiongkuo Min, Tian Han, Qiangqiang Zhou, Shaobo Yu, Yongqing Chen, Guangtao Zhai, Xiaokang Yang

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Generative Text Modeling through Short Run Inference.

Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020

Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling.

Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

CoRR, 2020

Learning Latent Space Energy-Based Prior Model for Molecule Generation.

Bo Pang, Tian Han, Ying Nian Wu

CoRR, 2020

Learning Latent Space Energy-Based Prior Model.

Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Saliency Prediction on Omnidirectional Images with Brain-Like Shallow Neural Network.

Dandan Zhu, Yongqing Chen, Xiongkuo Min, Defang Zhao, Yucheng Zhu, Qiangqiang Zhou, Xiaokang Yang, Tian Han

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Ransp: Ranking Attention Network For Saliency Prediction On Omnidirectional Images.

Dandan Zhu, Yongqing Chen, Tian Han, Defang Zhao, Yucheng Zhu, Qiangqiang Zhou, Guangtao Zhai, Xiaokang Yang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference.

Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Computer Vision - ECCV 2020, 2020

Joint Training of Variational Auto-Encoder and Latent Energy-Based Model.

Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models.

Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Unsupervised Learning and Understanding of Deep Generative Models.

Tian Han

PhD thesis, 2019

Replicating Neuroscience Observations on ML/MF and AM Face Patches by Deep Generative Model.

Tian Han, Xianglei Xing, Jiawen Wu, Ying Nian Wu

Neural Comput., 2019

Learning Deep Generative Models with Short Run Inference Dynamics.

Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu

CoRR, 2019

Deep Unsupervised Clustering with Clustered Generator Model.

Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu

CoRR, 2019

360 Degree Panorama Synthesis From Sequential Views Based on Improved FC-Densenets.

Dandan Zhu, Qiangqiang Zhou, Tian Han, Yongqing Chen

IEEE Access, 2019

Learning Generator Networks for Dynamic Patterns.

Tian Han, Yang Lu, Jiawen Wu, Xianglei Xing, Ying Nian Wu

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network.

Xianglei Xing, Tian Han, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model.

Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model.

Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu

CoRR, 2018

A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models.

Ying Nian Wu, Ruiqi Gao, Tian Han, Song-Chun Zhu

CoRR, 2018

Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry.

Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu

CoRR, 2018

Survey on person re-identification based on deep learning.

Kejun Wang, Haolin Wang, Meichen Liu, Xianglei Xing, Tian Han

CAAI Trans. Intell. Technol., 2018

Replicating Active Appearance Model by Generator Network.

Tian Han, Jiawen Wu, Ying Nian Wu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning Multi-view Generator Network for Shared Representation.

Tian Han, Xianglei Xing, Ying Nian Wu

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

Alternating Back-Propagation for Generator Network.

Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Learning Generative ConvNet with Continuous Latent Factors by Alternating Back-Propagation.

Tian Han, Yang Lu, Song-Chun Zhu, Ying Nian Wu

CoRR, 2016

2012

Parsing façade with rank-one approximation.

Chao Yang, Tian Han, Long Quan, Chiew-Lan Tai

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Quasi-regular Facade Structure Extraction.

Tian Han, Chun Liu, Chiew-Lan Tai, Long Quan

Proceedings of the Computer Vision, 2012