3 papers
cs.LG2026
BERTology of Molecular Property Prediction
Mohammad Mostafanejad, Paul Saxe, T. Daniel Crawford
Chemical language models (CLMs) have emerged as promising competitors to popular classical machine learning models for molecular property prediction (MPP) tasks. However, an increa…
physics.chem-ph2025
SEAMM: A Simulation Environment for Atomistic and Molecular Modeling
Paul Saxe, Jessica Nash, Mohammad Mostafanejad +4
The Simulation Environment for Atomistic and Molecular Modeling (SEAMM) is an open-source software package written in Python that provides a graphical interface for setting up, exe…
cs.LG2024
Unification of popular artificial neural network activation functions
Mohammad Mostafanejad
We present a unified representation of the most popular neural network activation functions. Adopting Mittag-Leffler functions of fractional calculus, we propose a flexible and com…