Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems. - Abishek Thangamuthu; Gunjan Kumar; Suresh Bishnoi; Ravinder Bhattoo; N. M. Anoop Krishnan; Sayan Ranu (NeurIPS, 2022)

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems. - Suresh Bishnoi; Ravinder Bhattoo; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2022)

Predicting Oxide Glass Properties with Low Complexity Neural Network and Physical and Chemical Descriptors. - Suresh Bishnoi; Skyler Badge; Jayadeva; N. M. Anoop Krishnan (CoRR, 2022)

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Physical Systems. - Suresh Bishnoi; Ravinder Bhattoo; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (ICLR, 2023)

Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics. - Suresh Bishnoi; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (CoRR, 2023)

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics. - Suresh Bishnoi; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (ICLR, 2024)

Discovering symbolic laws directly from trajectories with hamiltonian graph neural networks. - Suresh Bishnoi; Ravinder Bhattoo; Jayadeva; Sayan Ranu; N. M. Anoop Krishnan (Mach. Learn. Sci. Technol., 2024)