21 citations · 53 across the 8 of their papers we have counts for
3 papers · 1 filter
Symbolic Regression via Neural-Guided Genetic Programming Population Seeding
T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt +3
Symbolic regression is the process of identifying mathematical expressions that fit observed output from a black-box process. It is a discrete optimization problem generally believ…
Improving exploration in policy gradient search: Application to symbolic optimization
Mikel Landajuela, Brenden K. Petersen, Soo K. Kim +5
Many machine learning strategies designed to automate mathematical tasks leverage neural networks to search large combinatorial spaces of mathematical symbols. In contrast to tradi…
Reinforcement Learning for Adaptive Mesh Refinement
Jiachen Yang, Tarik Dzanic, Brenden Petersen +9
Large-scale finite element simulations of complex physical systems governed by partial differential equations (PDE) crucially depend on adaptive mesh refinement (AMR) to allocate c…