Expression Tree

Expression trees represent mathematical formulas as hierarchical structures, facilitating efficient manipulation and analysis. Current research focuses on automatically generating these trees from various inputs, including natural language descriptions of mathematical problems, sensor data (e.g., facial expressions or trajectories), and tabular data, employing techniques like deep symbolic regression, transformer architectures, and reinforcement learning algorithms such as Monte Carlo tree search. These advancements improve the accuracy and efficiency of solving mathematical problems, enabling applications in diverse fields like automated equation discovery, numerical reasoning in complex datasets, and improved human-computer interaction.