5 citations · 5 across the 3 of their papers we have counts for
3 papers · 1 filter
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics
Conor F. Hayes, Felipe Leno Da Silva, Jiachen Yang +15
Deep Symbolic Optimization (DSO) is a novel computational framework that enables symbolic optimization for scientific discovery, particularly in applications involving the search f…
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces
Jacob F. Pettit, Chak Shing Lee, Jiachen Yang +4
We consider the challenge of black-box optimization within hybrid discrete-continuous and variable-length spaces, a problem that arises in various applications, such as decision tr…
Incorporating domain knowledge into neural-guided search
Brenden K. Petersen, Claudio P. Santiago, Mikel Landajuela
Many AutoML problems involve optimizing discrete objects under a black-box reward. Neural-guided search provides a flexible means of searching these combinatorial spaces using an a…