DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
Liu et al.'s ICLR 2025 paper introducing DenoiseVAE, which learns adaptive, atom-specific noise for better molecular …...
Molecular-Representation
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
Lu et al. introduce SpaceFormer, a Transformer that models entire 3D molecular space—not just atoms—for superior …...
GEOM Dataset: 3D Molecular Conformer Generation
Learn how GEOM transforms 2D molecular graphs into dynamic 3D conformer ensembles for molecular machine learning …
Invalid SMILES are Beneficial Rather than Detrimental to Chemical Language Models
Skinnider (2024) shows that generating invalid SMILES actually improves chemical language model performance through …...
Synthetic Isomer Data Generation Pipeline
An end-to-end cheminformatics pipeline transforming 1D chemical formulas into 3D conformer datasets using graph …...
Can You Hear the Shape of a Molecule? (Part Three)
Supervised learning reveals hidden eigenvalue patterns that clustering missed, testing k-NN and logistic regression on …
Can You Hear the Shape of a Molecule? (Part Two)
Clustering analysis reveals why Coulomb matrix eigenvalues struggle with larger alkanes, using Dunn Index and silhouette …
Can You Hear the Shape of a Molecule?
Explore molecular shape recognition using Coulomb matrix eigenvalues. Analysis of alkane isomers from data generation to …
Understanding Coulomb Matrices for Molecular Machine Learning
Learn how Coulomb matrices encode 3D molecular structure for machine learning from basic theory to Python implementation …
SELFIES and the Future of Molecular String Representations
Perspective on SELFIES as a 100% robust SMILES alternative, with 16 future research directions for molecular AI....
IMG2SMI: Translating Molecular Structure Images to SMILES
Campos & Ji's method for converting 2D molecular images to SMILES strings using Transformers and SELFIES representation....