Ting Chen

According to our database, Ting Chen authored at least 37 papers between 2014 and 2023.

Collaborative distances:

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

2023

FIT: Far-reaching Interleaved Transformers.

Ting Chen, Lala Li

CoRR, 2023

Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning.

Ting Chen, Ruixiang Zhang, Geoffrey E. Hinton

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Generalist Framework for Panoptic Segmentation of Images and Videos.

Ting Chen, Lala Li, Saurabh Saxena, Geoffrey E. Hinton, David J. Fleet

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

2022

Decoder Denoising Pretraining for Semantic Segmentation.

Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi

Trans. Mach. Learn. Res., 2022

Robust and Efficient Medical Imaging with Self-Supervision.

Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, Yuan Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zachary Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Gregory S. Corrado, Dale R. Webster, David J. Fleet, Geoffrey E. Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan

CoRR, 2022

A Unified Sequence Interface for Vision Tasks.

Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton

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

Pix2seq: A Language Modeling Framework for Object Detection.

Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton

Proceedings of the Tenth International Conference on Learning Representations, 2022

Denoising Pretraining for Semantic Segmentation.

Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Why Do Better Loss Functions Lead to Less Transferable Features?

Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Intriguing Properties of Contrastive Losses.

Ting Chen, Calvin Luo, Lala Li

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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, Vivek Natarajan, Mohammad Norouzi

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Intriguing Properties of Contrastive Losses.

Ting Chen, Lala Li

CoRR, 2020

What's in a Loss Function for Image Classification?

Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi

CoRR, 2020

Big Self-Supervised Models are Strong Semi-Supervised Learners.

Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton

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

Differentiable Product Quantization for End-to-End Embedding Compression.

Ting Chen, Lala Li, Yizhou Sun

Proceedings of the 37th International Conference on Machine Learning, 2020

A Simple Framework for Contrastive Learning of Visual Representations.

Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Effective and Efficient Representation Learning for Graph Structures.

Ting Chen

PhD thesis, 2019

Differentiable Product Quantization for End-to-End Embedding Compression.

Ting Chen, Yizhou Sun

CoRR, 2019

Pre-Training Graph Neural Networks for Generic Structural Feature Extraction.

Ziniu Hu, Changjun Fan, Ting Chen, Kai-Wei Chang, Yizhou Sun

CoRR, 2019

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification.

Ting Chen, Song Bian, Yizhou Sun

CoRR, 2019

Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity.

Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, Wei Wang

CoRR, 2019

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation.

Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity.

Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, Wei Wang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Few-Shot Representation Learning for Out-Of-Vocabulary Words.

Ziniu Hu, Ting Chen, Kai-Wei Chang, Yizhou Sun

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Graph Edit Distance Computation via Graph Neural Networks.

Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang

CoRR, 2018

Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations.

Ting Chen, Martin Renqiang Min, Yizhou Sun

Proceedings of the 35th International Conference on Machine Learning, 2018

HeteroMed: Heterogeneous Information Network for Medical Diagnosis.

Anahita Hosseini, Ting Chen, Wenjun Wu, Yizhou Sun, Majid Sarrafzadeh

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Learning K-way D-dimensional Discrete Code For Compact Embedding Representations.

Ting Chen, Martin Renqiang Min, Yizhou Sun

CoRR, 2017

Joint Text Embedding for Personalized Content-based Recommendation.

Ting Chen, Liangjie Hong, Yue Shi, Yizhou Sun

CoRR, 2017

Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification.

Ting Chen, Yizhou Sun

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Ideology Detection for Twitter Users via Link Analysis.

Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang

Proceedings of the Social, Cultural, and Behavioral Modeling, 2017

On Sampling Strategies for Neural Network-based Collaborative Filtering.

Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

Ideology Detection for Twitter Users with Heterogeneous Types of Links.

Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang

CoRR, 2016

Integrating Community and Role Detection in Information Networks.

Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, Guofei Jiang

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events.

Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Kai Zhang

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

On Burst Detection and Prediction in Retweeting Sequence.

Zhilin Luo, Yue Wang, Xintao Wu, Wandong Cai, Ting Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

2014

Topic-factorized ideal point estimation model for legislative voting network.

Yupeng Gu, Yizhou Sun, Ning Jiang, Bingyu Wang, Ting Chen

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014