From the 1 of 11 linked papers with an AI index.
11 papers
PRIME: Protein Representation via Physics-Informed Multiscale Equivariant Hierarchies
Viet Thanh Duy Nguyen, John K. Johnstone, Truong-Son Hy
The paper presents PRIME, a physics‑informed multiscale hierarchical graph framework that models proteins at five structural levels and enables bidirectional information flow, achi…
Spectral Embeddings Leak Graph Topology: Theory, Benchmark, and Adaptive Reconstruction
Thinh Nguyen-Cong, Truong-Son Hy, Thang N. Dinh
Graph Neural Networks (GNNs) excel on relational data, but standard benchmarks unrealistically assume the graph is centrally available. In practice, settings such as Federated Grap…
DiFlowDubber: Discrete Flow Matching for Automated Video Dubbing via Cross-Modal Alignment and Synchronization
Ngoc-Son Nguyen, Thanh V. T. Tran, Jeongsoo Choi +3
Video dubbing requires content accuracy, expressive prosody, high-quality acoustics, and precise lip synchronization, yet existing approaches struggle on all four fronts. To addres…
Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization
Truong-Son Hy
Protein fitness optimization is inherently a discrete combinatorial problem, yet most learning-based approaches rely on continuous representations and are primarily evaluated throu…
Binary Latent Protein Fitness Landscapes for Quantum Annealing Optimization
Truong-Son Hy
We propose Q-BIOLAT, a framework for modeling and optimizing protein fitness landscapes in binary latent spaces. Starting from protein sequences, we leverage pretrained protein lan…
Halfway to 3D: Ensembling 2.5D and 3D Models for Robust COVID-19 CT Diagnosis
Tuan-Anh Yang, Bao V. Q. Bui, Chanh-Quang Vo-Van +1
We propose a deep learning framework for COVID-19 detection and disease classification from chest CT scans that integrates both 2.5D and 3D representations to capture complementary…