18 citations · 58 across the 14 of their papers we have counts for
15 papers
Flow Matching in Latent Space
Quan Dao, Hao Phung, Binh Nguyen +1
Flow matching is a recent framework to train generative models that exhibits impressive empirical performance while being relatively easier to train compared with diffusion-based m…
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Duy M. H. Nguyen, Hoang Nguyen, Nghiem T. Diep +9
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained dee…
Correlation visualization under missing values: a comparison between imputation and direct parameter estimation methods
Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu +4
Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating co…
Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction
Tu T. Do, Mai Anh Vu, Tuan L. Vo +6
Monotone missing data is a common problem in data analysis. However, imputation combined with dimensionality reduction can be computationally expensive, especially with the increas…
Application of Self-Supervised Learning to MICA Model for Reconstructing Imperfect 3D Facial Structures
Phuong D. Nguyen, Thinh D. Le, Duong Q. Nguyen +2
In this study, we emphasize the integration of a pre-trained MICA model with an imperfect face dataset, employing a self-supervised learning approach. We present an innovative meth…
Conditional expectation with regularization for missing data imputation
Mai Anh Vu, Thu Nguyen, Tu T. Do +5
Missing data frequently occurs in datasets across various domains, such as medicine, sports, and finance. In many cases, to enable proper and reliable analyses of such data, the mi…
Ontology-based Solution for Building an Intelligent Searching System on Traffic Law Documents
Vuong T. Pham, Hien D. Nguyen, Thinh Le +2
In this paper, an ontology-based approach is used to organize the knowledge base of legal documents in road traffic law. This knowledge model is built by the improvement of ontolog…
DRG-Net: Interactive Joint Learning of Multi-lesion Segmentation and Classification for Diabetic Retinopathy Grading
Hasan Md Tusfiqur, Duy M. H. Nguyen, Mai T. N. Truong +8
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world, and early DR detection is necessary to prevent vision loss and support an appropriate treatment. In this w…
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Duy M. H. Nguyen, Hoang Nguyen, Mai T. N. Truong +7
Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs i…
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
Thomas Moreau, Mathurin Massias, Alexandre Gramfort +18
Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.…
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot
Identifying the relevant variables for a classification model with correct confidence levels is a central but difficult task in high-dimension. Despite the core role of sparse logi…
Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding
Binh X. Nguyen, Binh D. Nguyen, Gustavo Carneiro +3
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample similarities in the embedding space from an unlabeled dataset. Traditional UDML methods usually use the tripl…
Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models
Binh An Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In recent years, Vietnamese Named Entity Recognition (NER) systems have had a great breakthrough when using Deep Neural Network methods. This paper describes the primary errors of…
LSTM Easy-first Dependency Parsing with Pre-trained Word Embeddings and Character-level Word Embeddings in Vietnamese
Binh Duc Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
In Vietnamese dependency parsing, several methods have been proposed. Dependency parser which uses deep neural network model has been reported that achieved state-of-the-art result…
Overcoming Data Limitation in Medical Visual Question Answering
Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen +3
Traditional approaches for Visual Question Answering (VQA) require large amount of labeled data for training. Unfortunately, such large scale data is usually not available for medi…