Tongzhou Wang

According to our database, Tongzhou Wang authored at least 24 papers between 2017 and 2024.

Collaborative distances:

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

2024

CycleGAN with Better Cycles.

Tongzhou Wang, Yihan Lin

CoRR, 2024

The Platonic Representation Hypothesis.

Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola

CoRR, 2024

Position: The Platonic Representation Hypothesis.

Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Characterizing Model Robustness via Natural Input Gradients.

Adrián Rodríguez-Muñoz, Tongzhou Wang, Antonio Torralba

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Deep Augmentation: Enhancing Self-Supervised Learning through Transformations in Higher Activation Space.

Rickard Brüel Gabrielsson, Tongzhou Wang, Manel Baradad, Justin Solomon

CoRR, 2023

Steerable Equivariant Representation Learning.

Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan

CoRR, 2023

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning.

Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang

Proceedings of the International Conference on Machine Learning, 2023

Generalizing Dataset Distillation via Deep Generative Prior.

George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings.

Tongzhou Wang, Phillip Isola

CoRR, 2022

On the Learning and Learnablity of Quasimetrics.

Tongzhou Wang, Phillip Isola

CoRR, 2022

Procedural Image Programs for Representation Learning.

Manel Baradad, Chun-Fu Richard Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola

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

Denoised MDPs: Learning World Models Better Than the World Itself.

Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian

Proceedings of the International Conference on Machine Learning, 2022

On the Learning and Learnability of Quasimetrics.

Tongzhou Wang, Phillip Isola

Proceedings of the Tenth International Conference on Learning Representations, 2022

Totems: Physical Objects for Verifying Visual Integrity.

Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba

Proceedings of the Computer Vision - ECCV 2022, 2022

Dataset Distillation by Matching Training Trajectories.

George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu

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

Wearable ImageNet: Synthesizing Tileable Textures via Dataset Distillation.

George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu

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

2021

Learning to See by Looking at Noise.

Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba

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

2020

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere.

Tongzhou Wang, Phillip Isola

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

Rewriting a Deep Generative Model.

David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba

Proceedings of the Computer Vision - ECCV 2020, 2020

Diverse Image Generation via Self-Conditioned GANs.

Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, Antonio Torralba

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2018

Dataset Distillation.

Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, Alexei A. Efros

CoRR, 2018

Meta-Learning MCMC Proposals.

Tongzhou Wang, Yi Wu, Dave Moore, Stuart J. Russell

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Neural Block Sampling.

Tongzhou Wang, Yi Wu, David A. Moore, Stuart J. Russell

CoRR, 2017

Learning to Synthesize a 4D RGBD Light Field from a Single Image.

Pratul P. Srinivasan, Tongzhou Wang, Ashwin Sreelal, Ravi Ramamoorthi, Ren Ng

Proceedings of the IEEE International Conference on Computer Vision, 2017