Yonglong Tian

According to our database¹, Yonglong Tian authored at least 40 papers between 2014 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2024

Self-Correcting Self-Consuming Loops for Generative Model Training.

[BibT_eX]

[DOI]

CoRR, 2024

Denoising Vision Transformers.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Learning Vision from Models Rivals Learning Vision from Data.

[BibT_eX]

[DOI]

CoRR, 2023

Scaling Laws of Synthetic Images for Model Training ... for Now.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency.

[BibT_eX]

[DOI]

CoRR, 2023

Addressing Feature Suppression in Unsupervised Visual Representations.

[BibT_eX]

[DOI]

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

Restart Sampling for Improving Generative Processes.

[BibT_eX]

[DOI]

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

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners.

[BibT_eX]

[DOI]

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

Improving CLIP Training with Language Rewrites.

[BibT_eX]

[DOI]

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

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-supervision through Random Segments with Autoregressive Coding (RandSAC).

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision?

[BibT_eX]

[DOI]

CoRR, 2022

Self-supervision through Random Segments with Autoregressive Coding (RandSAC).

[BibT_eX]

[DOI]

CoRR, 2022

Unsupervised Learning of Shape Programs with Repeatable Implicit Parts.

[BibT_eX]

[DOI]

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

Generative Models as a Data Source for Multiview Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Co-advise: Cross Inductive Bias Distillation.

[BibT_eX]

[DOI]

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

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate.

[BibT_eX]

[DOI]

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

2021

Simple Distillation Baselines for Improving Small Self-supervised Models.

[BibT_eX]

[DOI]

Jindong Gu

Wei Liu

Yonglong Tian

CoRR, 2021

Divide and Contrast: Self-supervised Learning from Uncurated Data.

[BibT_eX]

[DOI]

Yonglong Tian

Olivier J. Hénaff

Aäron van den Oord

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

Composable Augmentation Encoding for Video Representation Learning.

[BibT_eX]

[DOI]

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

2020

Information-Preserving Contrastive Learning for Self-Supervised Representations.

[BibT_eX]

[DOI]

CoRR, 2020

What Makes for Good Views for Contrastive Learning?

[BibT_eX]

[DOI]

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

Supervised Contrastive Learning.

[BibT_eX]

[DOI]

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

Contrastive Representation Distillation.

[BibT_eX]

[DOI]

Yonglong Tian

Dilip Krishnan

Phillip Isola

Proceedings of the 8th International Conference on Learning Representations, 2020

Rethinking Few-Shot Image Classification: A Good Embedding is All You Need?

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Contrastive Multiview Coding.

[BibT_eX]

[DOI]

Yonglong Tian

Dilip Krishnan

Phillip Isola

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Training-Free Uncertainty Estimation for Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Learning to Infer and Execute 3D Shape Programs.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

RF-Based Fall Monitoring Using Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

RF-based 3D skeletons.

[BibT_eX]

[DOI]

Mingmin Zhao

Yonglong Tian

Hang Zhao

Mohammad Abu Alsheikh

Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, 2018

Representation Learning on Graphs with Jumping Knowledge Networks.

[BibT_eX]

[DOI]

Ken-ichi Kawarabayashi

Stefanie Jegelka

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

Through-Wall Human Pose Estimation Using Radio Signals.

[BibT_eX]

[DOI]

Mingmin Zhao

Tianhong Li

Mohammad Abu Alsheikh

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2017

2015

Deep Learning Strong Parts for Pedestrian Detection.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Pedestrian detection aided by deep learning semantic tasks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

DeepID-Net: Deformable deep convolutional neural networks for object detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection.

[BibT_eX]

[DOI]

CoRR, 2014

Switchable Deep Network for Pedestrian Detection.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Yonglong Tian

Timeline

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