3 papers
cs.LG2026
Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion
Parthasarathy Suryanarayanan, Susanta Das, Shreyans Sethi +2
Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation. Prediction is challenging for machine learning models b…
cs.LG2025
STAR-VAE: Latent Variable Transformers for Scalable and Controllable Molecular Generation
Bum Chul Kwon, Ben Shapira, Moshiko Raboh +5
The chemical space of drug-like molecules is vast, motivating the development of generative models that must learn broad chemical distributions, enable conditional generation by ca…
q-bio.BM2024
Multi-view biomedical foundation models for molecule-target and property prediction
Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi +15
Quality molecular representations are key to foundation model development in bio-medical research. Previous efforts have typically focused on a single representation or molecular v…