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researcher

T. Nguyen

9 papers hereh-index 8537 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author7

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CV4
same name
  • T. Nguyen — 70 papers, h 19
  • T. Nguyen — 33 papers, h 35
  • T. Nguyen — 22 papers, h 17
  • T. Nguyen — 19 papers, h 5
  • T. Nguyen — 19 papers, h 7
  • T. Nguyen — 18 papers, h 22

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedSELF: Learning to Filter Noisy Labels with Self-Ensembling

55 citations · 63 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

Bidirectional Diffusion Bridge Models

Duc Kieu, Kien Do, Toan Nguyen +2

Diffusion bridges have shown potential in paired image-to-image (I2I) translation tasks. However, existing methods are limited by their unidirectional nature, requiring separate mo…

cs.CV2022★ 7 cited

Causal Inference via Style Transfer for Out-of-distribution Generalisation

Toan Nguyen, Kien Do, Duc Thanh Nguyen +2

Out-of-distribution (OOD) generalisation aims to build a model that can generalise well on an unseen target domain using knowledge from multiple source domains. To this end, the mo…

cs.CV2019★ 55 cited

SELF: Learning to Filter Noisy Labels with Self-Ensembling

Duc Tam Nguyen, Chaithanya Kumar Mummadi, Thi Phuong Nhung Ngo +3

Deep neural networks (DNNs) have been shown to over-fit a dataset when being trained with noisy labels for a long enough time. To overcome this problem, we present a simple and eff…

cs.CV2019

DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision

Duc Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi +4

Deep neural network (DNN) based salient object detection in images based on high-quality labels is expensive. Alternative unsupervised approaches rely on careful selection of multi…

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