124 citations · 173 across the 11 of their papers we have counts for
3 papers · 1 filter
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems
Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi +3
Recently, graph neural networks have been gaining a lot of attention to simulate dynamical systems due to their inductive nature leading to zero-shot generalizability. Similarly, p…
Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors
Suresh Bishnoi, Skyler Badge, Jayadeva +1
Due to their disordered structure, glasses present a unique challenge in predicting the composition-property relationships. Recently, several attempts have been made to predict the…
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems
Suresh Bishnoi, Ravinder Bhattoo, Sayan Ranu +1
Neural networks with physics based inductive biases such as Lagrangian neural networks (LNN), and Hamiltonian neural networks (HNN) learn the dynamics of physical systems by encodi…