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4 papers
MolSnap: Snap-Fast Molecular Generation with Latent Variational Mean Flow
Md Atik Ahamed, Qiang Ye, Qiang Cheng
Molecular generation conditioned on textual descriptions is a fundamental task in computational chemistry and drug discovery. Existing methods often struggle to simultaneously ensu…
RefiDiff: Progressive Refinement Diffusion for Efficient Missing Data Imputation
Md Atik Ahamed, Qiang Ye, Qiang Cheng
Missing values in high-dimensional, mixed-type datasets pose significant challenges for data imputation, particularly under Missing Not At Random (MNAR) mechanisms. Existing method…
Mol-CADiff: Causality-Aware Autoregressive Diffusion for Molecule Generation
Md Atik Ahamed, Qiang Ye, Qiang Cheng
The design of novel molecules with desired properties is a key challenge in drug discovery and materials science. Traditional methods rely on trial-and-error, while recent deep lea…
GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture
Md Atik Ahamed, Andrew Cheng, Qiang Ye +1
Graph Neural Networks (GNNs) have demonstrated remarkable success in various applications, yet they often struggle to capture long-range dependencies (LRD) effectively. This paper…