3 papers
cs.PL2026
DeCo: A Core Calculus for Incremental Functional Programming with Generic Data Types
Timon Böhler, Tobias Reinhard, David Richter +1
Incrementalization speeds up computations by avoiding unnecessary recomputations and by efficiently reusing previous results. While domain-specific techniques achieve impressive sp…
cs.LG2025
Prompting Neural-Guided Equation Discovery Based on Residuals
Jannis Brugger, Viktor Pfanschilling, David Richter +2
Neural-guided equation discovery systems use a data set as prompt and predict an equation that describes the data set without extensive search. However, if the equation does not me…
cs.AI2025
Neural-Guided Equation Discovery
Jannis Brugger, Mattia Cerrato, David Richter +4
Deep learning approaches are becoming increasingly attractive for equation discovery. We show the advantages and disadvantages of using neural-guided equation discovery by giving a…