632 citations · 2.1k across the 24 of their papers we have counts for
29 papers
CircuitGate: Logic-Consistent Circuit-Level Functional Modeling for And-Inverter Graphs
Qifan Zhang, Ruijie Li, Fangzhou Zhang +6
And-Inverter Graphs (AIGs) are fundamental representations for logic synthesis and verification in Electronic Design Automation (EDA). As structured representations of complex digi…
Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts
Christelle Schneuwly Diaz, Narmina Baghirova, Duy-Thanh Vu +4
Accurate diagnostic classification and disease-severity prediction for Alzheimer's disease are hampered by the incompleteness and heterogeneity of real-world clinical data. Left un…
High-dimensional Many-to-many-to-many Mediation Analysis
Tien Dat Nguyen, Trung Khang Tran, Cong Khanh Truong +3
We study high-dimensional mediation analysis in which exposures, mediators, and outcomes are all multivariate, and both exposures and mediators may be high-dimensional. We formaliz…
Generative Model via Quantile Assignment
Georgi Hrusanov, Oliver Y. Chén, Julien S. Bodelet
Deep Generative models (DGMs) play two key roles in modern machine learning: (i) producing new information (e.g., image synthesis) and (ii) reducing dimensionality. However, tradit…
Physics-Informed Neural Koopman Machine for Interpretable Longitudinal Personalized Alzheimer's Disease Forecasting
Georgi Hrusanov, Duy-Thanh Vu, Duy-Cat Can +6
Early forecasting of individual cognitive decline in Alzheimer's disease (AD) is central to disease evaluation and management. Despite advances, it is as of yet challenging for exi…
MUDI: A Multimodal Biomedical Dataset for Understanding Pharmacodynamic Drug-Drug Interactions
Tung-Lam Ngo, Ba-Hoang Tran, Duy-Cat Can +3
Understanding the interaction between different drugs (drug-drug interaction or DDI) is critical for ensuring patient safety and optimizing therapeutic outcomes. Existing DDI datas…
REMEMBER: Retrieval-based Explainable Multimodal Evidence-guided Modeling for Brain Evaluation and Reasoning in Zero- and Few-shot Neurodegenerative Diagnosis
Duy-Cat Can, Quang-Huy Tang, Huong Ha +2
Timely and accurate diagnosis of neurodegenerative disorders, such as Alzheimer's disease, is central to disease management. Existing deep learning models require large-scale annot…
Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction
Narmina Baghirova, Duy-Thanh Vũ, Duy-Cat Can +6
Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of cases. AD is associated with disru…
VisTA: Vision-Text Alignment Model with Contrastive Learning using Multimodal Data for Evidence-Driven, Reliable, and Explainable Alzheimer's Disease Diagnosis
Duy-Cat Can, Linh D. Dang, Quang-Huy Tang +5
Objective: Assessing Alzheimer's disease (AD) using high-dimensional radiology images is clinically important but challenging. Although Artificial Intelligence (AI) has advanced AD…
Enhancing Uncertain Demand Prediction in Hospitals Using Simple and Advanced Machine Learning
Annie Hu, Samuel Stockman, Xun Wu +3
Early and timely prediction of patient care demand not only affects effective resource allocation but also influences clinical decision-making as well as patient experience. Accura…
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging
Huy Phan, Kristian P. Lorenzen, Elisabeth Heremans +7
Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal dependency in the sleep data. Yet, exploring this long-term dependency when developing sle…
Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones
Oliver Y. Chén, Florian Lipsmeier, Huy Phan +5
Personalized longitudinal disease assessment is central to quickly diagnosing, appropriately managing, and optimally adapting the therapeutic strategy of multiple sclerosis (MS). I…
Uniting Machine Intelligence, Brain and Behavioural Sciences to Assist Criminal Justice
Oliver Y. Chén
I discuss here three important roles where machine intelligence, brain and behaviour studies together may facilitate criminal law. First, predictive modelling using brain and behav…
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification
Huy Phan, Kaare Mikkelsen, Oliver Y. Chén +3
Background: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments. Methods: Towards inter…
Multi-view Audio and Music Classification
Huy Phan, Huy Le Nguyen, Oliver Y. Chén +4
We propose in this work a multi-view learning approach for audio and music classification. Considering four typical low-level representations (i.e. different views) commonly used f…
Self-Attention Generative Adversarial Network for Speech Enhancement
Huy Phan, Huy Le Nguyen, Oliver Y. Chén +4
Existing generative adversarial networks (GANs) for speech enhancement solely rely on the convolution operation, which may obscure temporal dependencies across the sequence input.…
XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging
Huy Phan, Oliver Y. Chén, Minh C. Tran +3
Automating sleep staging is vital to scale up sleep assessment and diagnosis to serve millions experiencing sleep deprivation and disorders and enable longitudinal sleep monitoring…
Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization
Huy Phan, Kaare Mikkelsen, Oliver Y. Chén +4
Brain waves vary between people. An obvious way to improve automatic sleep staging for longitudinal sleep monitoring is personalization of algorithms based on individual characteri…
Statistical Quantile Learning for Large, Nonlinear, and Additive Latent Variable Models
Julien Bodelet, Guillaume Blanc, Jiajun Shan +2
The studies of large-scale, high-dimensional data in fields such as genomics and neuroscience have injected new insights into science. Yet, despite advances, they are confronting s…
Thou Shalt Not Reject the P-value
Oliver Y. Chén, Raúl G. Saraiva, Guy Nagels +9
Since its debut in the 18th century, the P-value has been an important part of hypothesis testing-based scientific discoveries. As the statistical engine accelerates, questions are…
Improving GANs for Speech Enhancement
Huy Phan, Ian V. McLoughlin, Lam Pham +4
Generative adversarial networks (GAN) have recently been shown to be efficient for speech enhancement. However, most, if not all, existing speech enhancement GANs (SEGAN) make use…
Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning
Huy Phan, Oliver Y. Chén, Philipp Koch +4
Background: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a…
Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch
Huy Phan, Oliver Y. Chén, Philipp Koch +2
Many sleep studies suffer from the problem of insufficient data to fully utilize deep neural networks as different labs use different recordings set ups, leading to the need of tra…
Spatio-Temporal Attention Pooling for Audio Scene Classification
Huy Phan, Oliver Y. Chén, Lam Pham +4
Acoustic scenes are rich and redundant in their content. In this work, we present a spatio-temporal attention pooling layer coupled with a convolutional recurrent neural network to…