4 papers · 1 filter
DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction
Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal +2
High-fidelity solubility prediction is fundamental to pharmaceutical development and environmental partitioning, where accurate modeling must couple molecular structure with thermo…
SC3: The Multi-Solvent Solubility Challenge and Benchmark
Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal +4
Solubility prediction is a standard benchmark in computational chemistry, yet multi-solvent models which reportedly approach the experimental-noise ceiling (i.e. the aleatoric limi…
On the Optimizer Dependence of Neural Scaling Laws
Vansh Ramani, Shourya Vir Jain
The scaling exponent in neural scaling laws is commonly treated as a fixed constant set by architecture and data. We present evidence that depends sys…
Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence
Mridul Gupta, Samyak Jain, Vansh Ramani +2
Graph Neural Networks (GNNs) are powerful tools for learning from graph-structured data, but their scalability is increasingly strained by the size of real-world graphs in domains…