Anh Tong

According to our database, Anh Tong authored at least 16 papers between 2016 and 2026.

Collaborative distances:

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

2026

Towards Transparent Time Series Analysis: Exploring Methods and Enhancing Interpretability.

Youngjin Park, Anh Tong, Sehyun Lee, Jihyeon Seong, Qin Xie, Jaesik Choi

ACM Comput. Surv., July, 2026

LoCO: Low-rank Compositional Rotation Fine-tuning.

An Nguyen, Jaesik Choi, Anh Tong

CoRR, May, 2026

Refining Compositional Diffusion for Reliable Long-Horizon Planning.

Kyowoon Lee, Yunhao Luo, Anh Tong, Jaesik Choi

CoRR, May, 2026

Cortex 2.0: Grounding World Models in Real-World Industrial Deployment.

Adriana Aida, Walid Amer, Katarina Bankovic, Dhruv Behl, Fabian Busch, Annie Bhalla, Minh Duong, Florian Gienger, Rohan Godse, Denis Grachev, Ralf Gulde, Elisa Hagensieker, Junpeng Hu, Shivam Joshi, Tobias Knobloch, Likith Kumar, Damien LaRocque, Keerthana Lokesh, Omar Moured, Khiem Nguyen, Christian Preyss, Ranjith Sriganesan, Vikram Singh, Carsten Sponner, Anh Tong, Dominik Tuscher, Marc Tuscher, Pavan Upputuri

CoRR, April, 2026

2025

Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning.

Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan M. Tran, David Leo Wright Hall, Cheongwoong Kang, Jaesik Choi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift.

Anh T. Nguyen, Lam Tran, Anh Tong, Tuan-Duy H. Nguyen, Toan Tran

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2023

Global Contrastive Learning for Long-Tailed Classification.

Thong Bach, Anh Tong, Truong Son Hy, Vu Nguyen, Thanh Nguyen-Tang

Trans. Mach. Learn. Res., 2023

Conditional Support Alignment for Domain Adaptation with Label Shift.

Anh T. Nguyen, Lam Tran, Anh Tong, Tuan-Duy H. Nguyen, Toan Tran

CoRR, 2023

SigFormer: Signature Transformers for Deep Hedging.

Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

2022

Learning Fractional White Noises in Neural Stochastic Differential Equations.

Anh Tong, Thanh Nguyen-Tang, Toan M. Tran, Jaesik Choi

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

2021

Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior.

Anh Tong, Toan M. Tran, Hung Bui, Jaesik Choi

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems.

Anh Tong, Jaesik Choi

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes.

Jiyeon Han, Kyowoon Lee, Anh Tong, Jaesik Choi

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

Discovering Latent Covariance Structures for Multiple Time Series.

Anh Tong, Jaesik Choi

Proceedings of the 36th International Conference on Machine Learning, 2019

2016

Searching for Topological Symmetry in Data Haystack.

Kallol Roy, Anh Tong, Jaesik Choi

CoRR, 2016

Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series.

Yunseong Hwang, Anh Tong, Jaesik Choi

Proceedings of the 33nd International Conference on Machine Learning, 2016