I joined Google Brain in 2019 as a Research Scientist. On March 2019, I received my Ph.D. degree from Department of Computer Science at UCLA. My research interests are in deep learning and artificial intelligence in general. I can be reached via email, or LinkedIn, or Twitter.
- Aug. 2019 - Differentiable Product Quantization for End-to-End Embedding Compression is on arxiv.
- May 2019 - Few-Shot Representation Learning for Out-Of-Vocabulary Words is accepted by ALC'19.
- May 2019 - Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification is on arxiv.
- Mar. 2019 - I completed my Ph.D. under supervision of Prof. Yizhou Sun.
Research Interests and Highlights
Discrete Structures and Efficient Modeling
Selected Recent Publications
- Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby, "Self-Supervised GANs via Auxiliary Rotation Loss" Conference on Computer Vision and Pattern Recognition (CVPR'19), Long Beach, USA, June 2019. [code]
- Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly, "On Self Modulation for Generative Adversarial Networks" Seventh International Conference on Learning Representations (ICLR'19), NewOrleans, USA, May 2019. [code]
- Ting Chen, Martin Renqiang Min, Yizhou Sun, "Learning K-way D-dimensional Discrete Codes For Compact Embedding Representations" Thirty-fifth International Conference on Machine Learning (ICML'18), Stockholm, Sweden, July 2018. [code]
- Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong, "On Sampling Strategies for Neural Network-based Collaborative Filtering," Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17), Halifax, Nova Scotia, Canada, Aug 2017. [code, slides, video]
- Ting Chen and Yizhou Sun, "Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification," Proc. of 2017 ACM Int. Conf. on Web Search and Data Mining (WSDM'17), Cambridge, UK, Feb 2017. [code, data]
- Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Kai Zhang, "Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events," Proc. 25th Int. Joint Conf. on Artifical Intelligence (IJCAI'16), New York City, USA, Jul 2016. [code upon request, slides]