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ORCIDTing Chen 0007
Person information
- affiliation: Google Brain
- affiliation (PhD 2019): University of California, Los Angeles, USA
- affiliation (former): Northeastern University, Boston, USA
Other persons with the same name
- Ting Chen — disambiguation page
- Ting Chen 0001
![[0000-0001-8414-6346]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-8414-6346")
— NYU Langone Health, Department of Radiation Oncology, NY, USA (and 3 more) - Ting Chen 0002 — University of Electronic Science and Technology of China, School of Computer Science and Engineering, Chengdu, China
- Ting Chen 0003 — Chang'an University, School of Information Engineering, Xi'an, China (and 2 more)
- Ting Chen 0004 — Vrije Universiteit Brussels, Department Electronics and Informatics, AVSP Lab, Belgium (and 1 more)
- Ting Chen 0005 — Autonomous University of Barcelona, Department of Mathematics, Spain (and 1 more)
- Ting Chen 0006 — Tsinghua University, Beijing, China (and 2 more)
- Ting Chen 0008 (aka: Ting Brendan Chen) — University of Western Brittany, Brest, France
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2020 – today
- 2023
[c23]Ting Chen, Lala Li, Saurabh Saxena, Geoffrey E. Hinton, David J. Fleet:
A Generalist Framework for Panoptic Segmentation of Images and Videos. ICCV 2023: 909-919- [c22]Ting Chen, Ruixiang Zhang, Geoffrey E. Hinton:
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning. ICLR 2023 - [i26]Ting Chen, Lala Li:
FIT: Far-reaching Interleaved Transformers. CoRR abs/2305.12689 (2023) - 2022
- [j1]Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi:
Decoder Denoising Pretraining for Semantic Segmentation. Trans. Mach. Learn. Res. 2022 (2022) - [c21]Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi:
Denoising Pretraining for Semantic Segmentation. CVPR Workshops 2022: 4174-4185 - [c20]Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton:
Pix2seq: A Language Modeling Framework for Object Detection. ICLR 2022 - [c19]Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton:
A Unified Sequence Interface for Vision Tasks. NeurIPS 2022 - [i25]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:
Robust and Efficient Medical Imaging with Self-Supervision. CoRR abs/2205.09723 (2022) - [i24]Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi:
Decoder Denoising Pretraining for Semantic Segmentation. CoRR abs/2205.11423 (2022) - [i23]Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton:
A Unified Sequence Interface for Vision Tasks. CoRR abs/2206.07669 (2022) - [i22]Ting Chen, Ruixiang Zhang, Geoffrey E. Hinton:
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning. CoRR abs/2208.04202 (2022) - [i21]Ting Chen, Lala Li, Saurabh Saxena, Geoffrey E. Hinton, David J. Fleet:
A Generalist Framework for Panoptic Segmentation of Images and Videos. CoRR abs/2210.06366 (2022) - 2021
- [c18]Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi:
Big Self-Supervised Models Advance Medical Image Classification. ICCV 2021: 3458-3468 - [c17]Ting Chen, Calvin Luo, Lala Li:
Intriguing Properties of Contrastive Losses. NeurIPS 2021: 11834-11845 - [c16]Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi:
Why Do Better Loss Functions Lead to Less Transferable Features? NeurIPS 2021: 28648-28662 - [i20]Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi:
Big Self-Supervised Models Advance Medical Image Classification. CoRR abs/2101.05224 (2021) - [i19]Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton:
Pix2seq: A Language Modeling Framework for Object Detection. CoRR abs/2109.10852 (2021) - 2020
- [c15]Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton:
A Simple Framework for Contrastive Learning of Visual Representations. ICML 2020: 1597-1607 - [c14]Ting Chen, Lala Li, Yizhou Sun:
Differentiable Product Quantization for End-to-End Embedding Compression. ICML 2020: 1617-1626 - [c13]Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton:
Big Self-Supervised Models are Strong Semi-Supervised Learners. NeurIPS 2020 - [i18]Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton:
A Simple Framework for Contrastive Learning of Visual Representations. CoRR abs/2002.05709 (2020) - [i17]Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton:
Big Self-Supervised Models are Strong Semi-Supervised Learners. CoRR abs/2006.10029 (2020) - [i16]Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi:
What's in a Loss Function for Image Classification? CoRR abs/2010.16402 (2020) - [i15]Ting Chen, Lala Li:
Intriguing Properties of Contrastive Losses. CoRR abs/2011.02803 (2020)
2010 – 2019
- 2019
- [b1]Ting Chen:
Effective and Efficient Representation Learning for Graph Structures. University of California, Los Angeles, USA, 2019 - [c12]Ziniu Hu, Ting Chen, Kai-Wei Chang, Yizhou Sun:
Few-Shot Representation Learning for Out-Of-Vocabulary Words. ACL (1) 2019: 4102-4112 - [c11]Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, Wei Wang:
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity. IJCAI 2019: 1988-1994 - [c10]Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang:
SimGNN: A Neural Network Approach to Fast Graph Similarity Computation. WSDM 2019: 384-392 - [i14]Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, Wei Wang:
Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity. CoRR abs/1904.01098 (2019) - [i13]Ting Chen, Song Bian, Yizhou Sun:
Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification. CoRR abs/1905.04579 (2019) - [i12]Ziniu Hu, Changjun Fan, Ting Chen, Kai-Wei Chang, Yizhou Sun:
Pre-Training Graph Neural Networks for Generic Structural Feature Extraction. CoRR abs/1905.13728 (2019) - [i11]Ziniu Hu, Ting Chen, Kai-Wei Chang, Yizhou Sun:
Few-Shot Representation Learning for Out-Of-Vocabulary Words. CoRR abs/1907.00505 (2019) - [i10]Ting Chen, Yizhou Sun:
Differentiable Product Quantization for End-to-End Embedding Compression. CoRR abs/1908.09756 (2019) - 2018
- [c9]Anahita Hosseini, Ting Chen, Wenjun Wu, Yizhou Sun, Majid Sarrafzadeh:
HeteroMed: Heterogeneous Information Network for Medical Diagnosis. CIKM 2018: 763-772 - [c8]Ting Chen, Martin Renqiang Min, Yizhou Sun:
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. ICML 2018: 853-862 - [i9]Anahita Hosseini, Ting Chen, Wenjun Wu, Yizhou Sun, Majid Sarrafzadeh:
HeteroMed: Heterogeneous Information Network for Medical Diagnosis. CoRR abs/1804.08052 (2018) - [i8]Ting Chen, Martin Renqiang Min, Yizhou Sun:
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. CoRR abs/1806.09464 (2018) - [i7]Yunsheng Bai, Hao Ding, Song Bian, Ting Chen, Yizhou Sun, Wei Wang:
Graph Edit Distance Computation via Graph Neural Networks. CoRR abs/1808.05689 (2018) - 2017
- [c7]Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong:
On Sampling Strategies for Neural Network-based Collaborative Filtering. KDD 2017: 767-776 - [c6]Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang:
Ideology Detection for Twitter Users via Link Analysis. SBP-BRiMS 2017: 262-268 - [c5]Ting Chen, Yizhou Sun:
Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification. WSDM 2017: 295-304 - [i6]Ting Chen, Liangjie Hong, Yue Shi, Yizhou Sun:
Joint Text Embedding for Personalized Content-based Recommendation. CoRR abs/1706.01084 (2017) - [i5]Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong:
On Sampling Strategies for Neural Network-based Collaborative Filtering. CoRR abs/1706.07881 (2017) - [i4]Ting Chen, Martin Renqiang Min, Yizhou Sun:
Learning K-way D-dimensional Discrete Code For Compact Embedding Representations. CoRR abs/1711.03067 (2017) - 2016
- [c4]Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Kai Zhang:
Entity Embedding-Based Anomaly Detection for Heterogeneous Categorical Events. IJCAI 2016: 1396-1403 - [c3]Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, Guofei Jiang:
Integrating Community and Role Detection in Information Networks. SDM 2016: 72-80 - [i3]Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Kai Zhang:
Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events. CoRR abs/1608.07502 (2016) - [i2]Ting Chen, Yizhou Sun:
Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification. CoRR abs/1612.02814 (2016) - [i1]Yupeng Gu, Ting Chen, Yizhou Sun, Bingyu Wang:
Ideology Detection for Twitter Users with Heterogeneous Types of Links. CoRR abs/1612.08207 (2016) - 2015
- [c2]Zhilin Luo, Yue Wang, Xintao Wu, Wandong Cai, Ting Chen:
On Burst Detection and Prediction in Retweeting Sequence. PAKDD (1) 2015: 96-107 - 2014
- [c1]Yupeng Gu, Yizhou Sun, Ning Jiang, Bingyu Wang, Ting Chen:
Topic-factorized ideal point estimation model for legislative voting network. KDD 2014: 183-192
Coauthor Index
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