51 citations · 65 across the 6 of their papers we have counts for
4 papers · 1 filter
One-Shot Transfer Learning of Physics-Informed Neural Networks
Shaan Desai, Marios Mattheakis, Hayden Joy +2
Solving differential equations efficiently and accurately sits at the heart of progress in many areas of scientific research, from classical dynamical systems to quantum mechanics.…
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems
Shaan Desai, Marios Mattheakis, David Sondak +2
Accurately learning the temporal behavior of dynamical systems requires models with well-chosen learning biases. Recent innovations embed the Hamiltonian and Lagrangian formalisms…
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL
Jack Parker-Holder, Vu Nguyen, Shaan Desai +1
Despite a series of recent successes in reinforcement learning (RL), many RL algorithms remain sensitive to hyperparameters. As such, there has recently been interest in the field…
Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems
Shaan Desai, Marios Mattheakis, Stephen Roberts
Recent advances show that neural networks embedded with physics-informed priors significantly outperform vanilla neural networks in learning and predicting the long term dynamics o…