Molecular AI Comparison Hub
4 papers - avg viability 6.5
Top Papers
- Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation(8.0)
Introducing a novel canonical diffusion framework for efficient and expressive molecular graph generation.
- Context-aware Graph Causality Inference for Few-Shot Molecular Property Prediction(7.0)
CaMol enhances molecular property prediction by using causality-driven graph learning for few-shot scenarios in drug discovery.
- Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding(6.0)
EDT-Former enhances Large Language Models for efficient molecular understanding without costly fine-tuning.
- MARA: Continuous SE(3)-Equivariant Attention for Molecular Force Fields(5.0)
MARA enhances molecular force field models by providing a more flexible and accurate SE(3)-equivariant attention mechanism.