Harmonia: A Unified Architecture for Efficient Deep Symbolic Regression
Symbolic regression (SR), the process of formulating a mathematical expression based on
observed data points, is a fundamental task in artificial intelligence but is often hindered by …
observed data points, is a fundamental task in artificial intelligence but is often hindered by …
Pareto Front Training For Multi-Objective Symbolic Optimization
Although Symbolic Optimization (SO) solutions have successfully been used in applications
ranging from Neural Architecture Search to Antibody Therapeutics Optimization, current SO …
ranging from Neural Architecture Search to Antibody Therapeutics Optimization, current SO …
Generative Design of Decision Tree Policies for Reinforcement Learning
Decision trees are an attractive choice for modeling policies in control environments due to
their interpretability, conciseness, and ease of implementation. However, generating …
their interpretability, conciseness, and ease of implementation. However, generating …
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces
In this paper, we consider the challenge of optimizing within hybrid discrete-continuous
spaces, a problem that arises in various important applications, such as symbolic regression …
spaces, a problem that arises in various important applications, such as symbolic regression …