2 papers
cs.LG2026
GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond
Parth Verma, Parv P. Singh, Vipul Garg +3
Graph Neural Networks (GNNs) have revolutionized Neural Force Fields for atomistic simulations, achieving near-quantum accuracy at reduced cost, yet adapting these models to new ch…
cs.LG2025
GNNMerge: Merging of GNN Models Without Accessing Training Data
Vipul Garg, Ishita Thakre, Sayan Ranu
Model merging has gained prominence in machine learning as a method to integrate multiple trained models into a single model without accessing the original training data. While exi…