Topic-factorized ideal point estimation model for legislative voting network. - Yupeng Gu; Yizhou Sun; Ning Jiang; Bingyu Wang; Ting Chen 007 (KDD, 2014)

On Burst Detection and Prediction in Retweeting Sequence. - Zhilin Luo; Yue Wang 009; Xintao Wu; Wandong Cai; Ting Chen 007 (PAKDD (1), 2015)

Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events. - Ting Chen 007; Lu-An Tang; Yizhou Sun; Zhengzhang Chen; Kai Zhang 001 (IJCAI, 2016)

Integrating Community and Role Detection in Information Networks. - Ting Chen 007; Lu-An Tang; Yizhou Sun; Zhengzhang Chen; Haifeng Chen; Guofei Jiang (SDM, 2016)

Ideology Detection for Twitter Users with Heterogeneous Types of Links. - Yupeng Gu; Ting Chen 007; Yizhou Sun; Bingyu Wang (CoRR, 2016)

On Sampling Strategies for Neural Network-based Collaborative Filtering. - Ting Chen 007; Yizhou Sun; Yue Shi 002; Liangjie Hong (KDD, 2017)

Ideology Detection for Twitter Users via Link Analysis. - Yupeng Gu; Ting Chen 007; Yizhou Sun; Bingyu Wang (SBP-BRiMS, 2017)

Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification. - Ting Chen 007; Yizhou Sun (WSDM, 2017)

Joint Text Embedding for Personalized Content-based Recommendation. - Ting Chen 007; Liangjie Hong; Yue Shi 002; Yizhou Sun (CoRR, 2017)

Learning K-way D-dimensional Discrete Code For Compact Embedding Representations. - Ting Chen 007; Martin Renqiang Min; Yizhou Sun (CoRR, 2017)

HeteroMed: Heterogeneous Information Network for Medical Diagnosis. - Anahita Hosseini; Ting Chen 007; Wenjun Wu; Yizhou Sun; Majid Sarrafzadeh (CIKM, 2018)

Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. - Ting Chen 007; Martin Renqiang Min; Yizhou Sun (ICML, 2018)

Graph Edit Distance Computation via Graph Neural Networks. - Yunsheng Bai; Hao Ding 003; Song Bian 002; Ting Chen 007; Yizhou Sun; Wei Wang 010 (CoRR, 2018)

Few-Shot Representation Learning for Out-Of-Vocabulary Words. - Ziniu Hu; Ting Chen 007; Kai-Wei Chang; Yizhou Sun (ACL (1), 2019)

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity. - Yunsheng Bai; Hao Ding 003; Yang Qiao; Agustin Marinovic; Ken Gu; Ting Chen 007; Yizhou Sun; Wei Wang 010 (IJCAI, 2019)

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation. - Yunsheng Bai; Hao Ding 003; Song Bian 002; Ting Chen 007; Yizhou Sun; Wei Wang 010 (WSDM, 2019)

Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity. - Yunsheng Bai; Hao Ding 003; Yang Qiao; Agustin Marinovic; Ken Gu; Ting Chen 007; Yizhou Sun; Wei Wang 010 (CoRR, 2019)

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification. - Ting Chen 007; Song Bian 002; Yizhou Sun (CoRR, 2019)

Pre-Training Graph Neural Networks for Generic Structural Feature Extraction. - Ziniu Hu; Changjun Fan; Ting Chen 007; Kai-Wei Chang; Yizhou Sun (CoRR, 2019)

Differentiable Product Quantization for End-to-End Embedding Compression. - Ting Chen 007; Yizhou Sun (CoRR, 2019)

Effective and Efficient Representation Learning for Graph Structures. - Ting Chen 007 (2019)

A Simple Framework for Contrastive Learning of Visual Representations. - Ting Chen 007; Simon Kornblith; Mohammad Norouzi 002; Geoffrey E. Hinton (ICML, 2020)

Differentiable Product Quantization for End-to-End Embedding Compression. - Ting Chen 007; Lala Li; Yizhou Sun (ICML, 2020)

Big Self-Supervised Models are Strong Semi-Supervised Learners. - Ting Chen 007; Simon Kornblith; Kevin Swersky; Mohammad Norouzi 002; Geoffrey E. Hinton (NeurIPS, 2020)

What's in a Loss Function for Image Classification? - Simon Kornblith; Honglak Lee; Ting Chen 007; Mohammad Norouzi 002 (CoRR, 2020)

Intriguing Properties of Contrastive Losses. - Ting Chen 007; Lala Li (CoRR, 2020)

Big Self-Supervised Models Advance Medical Image Classification. - Shekoofeh Azizi; Basil Mustafa; Fiona Ryan; Zachary Beaver; Jan Freyberg; Jonathan Deaton; Aaron Loh; Alan Karthikesalingam; Simon Kornblith; Ting Chen 007; Vivek Natarajan; Mohammad Norouzi 002 (ICCV, 2021)

Intriguing Properties of Contrastive Losses. - Ting Chen 007; Calvin Luo; Lala Li (NeurIPS, 2021)

Why Do Better Loss Functions Lead to Less Transferable Features? - Simon Kornblith; Ting Chen 007; Honglak Lee; Mohammad Norouzi 002 (NeurIPS, 2021)

Denoising Pretraining for Semantic Segmentation. - Emmanuel Asiedu Brempong; Simon Kornblith; Ting Chen 007; Niki Parmar; Matthias Minderer; Mohammad Norouzi 002 (CVPR Workshops, 2022)

Pix2seq: A Language Modeling Framework for Object Detection. - Ting Chen 007; Saurabh Saxena; Lala Li; David J. Fleet; Geoffrey E. Hinton (ICLR, 2022)

A Unified Sequence Interface for Vision Tasks. - Ting Chen 007; Saurabh Saxena; Lala Li; Tsung-Yi Lin; David J. Fleet; Geoffrey E. Hinton (NeurIPS, 2022)

Robust and Efficient Medical Imaging with Self-Supervision. - Shekoofeh Azizi; Laura Culp; Jan Freyberg; Basil Mustafa; Sebastien Baur; Simon Kornblith; Ting Chen 007; Patricia MacWilliams; S. Sara Mahdavi; Ellery Wulczyn; Boris Babenko; Megan Wilson; et al. (CoRR, 2022)

Decoder Denoising Pretraining for Semantic Segmentation. - Emmanuel Asiedu Brempong; Simon Kornblith; Ting Chen 007; Niki Parmar; Matthias Minderer; Mohammad Norouzi 002 (Trans. Mach. Learn. Res., 2022)

A Generalist Framework for Panoptic Segmentation of Images and Videos. - Ting Chen 007; Lala Li; Saurabh Saxena; Geoffrey E. Hinton; David J. Fleet (ICCV, 2023)

Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning. - Ting Chen 007; Ruixiang Zhang; Geoffrey E. Hinton (ICLR, 2023)

FIT: Far-reaching Interleaved Transformers. - Ting Chen 007; Lala Li (CoRR, 2023)