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Ai Drug Discovery

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Ai Drug Discovery

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Research Frontiers in Generative Models for Molecular Structure

Creating variational autoencoders and diffusion models to generate new bioactive molecules with specific therapeutic targets.

Latent Space Geometry in Molecular Generation Models
Diffusion-Based De Novo Synthesis of Bioactive Scaffolds
Equivariant Graph Networks for 3D Protein-Ligand Binding
Multi-Objective Generative Optimization at Drug-Like Boundaries
Flow-Matching Architectures for Constrained Chemical Space
Self-Supervised Learning in Unlabeled Molecular Distributions
Generative Models Bridging 2D Structures to Physicochemical Properties
Adversarial Robustness in Molecular Design Networks
Transformer-Based Generative Models for Polypharmacology Design
Uncertainty Quantification in Neural Molecular Scaffold Generation

All AI Drug Discovery PhD categories