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Tuan Nguyen

Associate Member (PhD), started 2020

Tuan Nguyen is a DPhil student in the CS Department at Oxford University, supervised by Dr. Gunes Baydin and co-supervised by Prof. Yarin Gal. His research interests include Bayesian Deep Learning, Efficient Inference, Representation Learning, and Interpretable Machine Learning. Before joining Oxford, he received his MSc in Computer Science from Korea Advanced Institute of Science and Technology.

Publications while at OATMLNews items mentioning Tuan NguyenReproducibility and CodeBlog Posts

Publications while at OATML:

KL Guided Domain Adaptation

Domain adaptation is an important problem and often needed for real-world applications. In this problem, instead of i.i.d. training and testing datapoints, we assume that the source (training) data and the target (testing) data have different distributions. With that setting, the empirical risk minimization training procedure often does not perform well, since it does not account for the change in the distribution. A common approach in the domain adaptation literature is to learn a representation of the input that has the same (marginal) distribution over the source and the target domain. However, these approaches often require additional networks and/or optimizing an adversarial (minimax) objective, which can be very expensive or unstable in practice. To improve upon these marginal alignment techniques, in this paper, we first derive a generalization bound for the target loss based on the training loss and the reverse Kullback-Leibler (KL) divergence between the source and the tar... [full abstract]

Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atılım Güneş Baydin
International Conference on Learning Representations, 2022
[arXiv] [BibTex]
More publications on Google Scholar.

Blog Posts

OATML at ICLR 2022

OATML group members and collaborators are proud to present 4 papers at ICLR 2022 main conference. …

Full post...

Yarin Gal, Tuan Nguyen, Andrew Jesson, Pascal Notin, Atılım Güneş Baydin, Clare Lyle, Milad Alizadeh, Joost van Amersfoort, Sebastian Farquhar, Muhammed Razzak, Freddie Kalaitzis, 01 Feb 2022

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