Tan M. Nguyen

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 31

Top Topics

Differential Equations

Principal Component Analysis

Top Venues

IEEE J. Sel. Top. Signal Process.

Publications

Rachel S. Y. Teo, Tan M. Nguyen
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis. CoRR (2024)
Tam Nguyen, César A. Uribe, Tan M. Nguyen, Richard G. Baraniuk
PIDformer: Transformer Meets Control Theory. CoRR (2024)
Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
A Primal-Dual Framework for Transformers and Neural Networks. CoRR (2024)
Stefan K. Nielsen, Laziz U. Abdullaev, Rachel S. Y. Teo, Tan M. Nguyen
Elliptical Attention. CoRR (2024)
Viet-Hoang Tran, Trang Pham, Tho Tran, Tam Le, Tan M. Nguyen
Tree-Sliced Wasserstein Distance on a System of Lines. CoRR (2024)
Son Nguyen, Cuong Tran Manh, Trung Kien Tran, Tan M. Nguyen, Thu-Trang Nguyen, Kien-Tuan Ngo, Hieu Dinh Vo
ARist: An effective API argument recommendation approach. J. Syst. Softw. 204 (2023)
Tam Nguyen, Tan M. Nguyen, Richard G. Baraniuk
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. CoRR (2023)
Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP (2023)
Khang Nguyen, Hieu Nong, Khuong Nguyen, Tan M. Nguyen, Vinh Nguyen
DeepGRAND: Deep Graph Neural Diffusion. ACSSC (2023)
Tuan Nguyen, Tam Nguyen, Vinh Nguyen, Tan M. Nguyen
p-Laplacian Transformer. CoRR (2023)
Son Nguyen, Cuong Tran Manh, Kien T. Tran, Tan M. Nguyen, Thu-Trang Nguyen, Kien-Tuan Ngo, Hieu Dinh Vo
ARIST: An Effective API Argument Recommendation Approach. CoRR (2023)
Tuan Nguyen, Tan M. Nguyen, Hirotada Honda, Takashi Sano, Vinh Nguyen, Shugo Nakamura
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach. CoRR (2023)
Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. 15 (2) (2022)
Tan M. Nguyen, Vai Suliafu, Stanley J. Osher, Long Chen, Bao Wang
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention. NeurIPS (2021)
Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
Heavy Ball Neural Ordinary Differential Equations. NeurIPS (2021)
Tam Nguyen, Tan M. Nguyen, Dung Le, Khuong Nguyen, Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
Transformer with a Mixture of Gaussian Keys. CoRR (2021)
Bao Wang, Hedi Xia, Tan M. Nguyen, Stanley J. Osher
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies. CoRR (2021)
Tan M. Nguyen, Vai Suliafu, Stanley J. Osher, Long Chen, Bao Wang
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention. CoRR (2021)
Tran Manh Cuong, Trung Kien Tran, Tan M. Nguyen, Thu-Trang Nguyen, Son Nguyen, Hieu Dinh Vo
API parameter recommendation based on language model and program analysis. APSEC (2021)
Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
Heavy Ball Neural Ordinary Differential Equations. CoRR (2021)
Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. IEEE J. Sel. Top. Signal Process. 14 (4) (2020)
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar
Neural Networks with Recurrent Generative Feedback. CoRR (2020)
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar
Neural Networks with Recurrent Generative Feedback. NeurIPS (2020)
Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
MomentumRNN: Integrating Momentum into Recurrent Neural Networks. CoRR (2020)
Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
MomentumRNN: Integrating Momentum into Recurrent Neural Networks. NeurIPS (2020)
Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. CoRR (2020)
Yujia Huang, Sihui Dai, Tan M. Nguyen, Richard G. Baraniuk, Anima Anandkumar
Out-of-Distribution Detection Using Neural Rendering Generative Models. CoRR (2019)
Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. CoRR (2019)
Tan M. Nguyen, Nan Ye, Peter L. Bartlett
Learning Near-optimal Convex Combinations of Basis Models with Generalization Guarantees. CoRR (2019)
Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference. CoRR (2019)
Nhat Ho, Tan M. Nguyen, Ankit B. Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk
Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. CoRR (2018)