The methods for symbolic regression (SR) have come a long way since the days of Koza-style genetic programming (GP). Our goal with this project is to keep a living benchmark of modern symbolic ...

Fraud detection in banking transactions is critical due to the surge in digital transactions and associated fraudulent activities. For imbalanced datasets, conventional machine learning models yield ...

These insights could help scientists build models that are simpler, more efficient, and possibly more transparent. More information: Vittorio Erba et al, Bilinear Sequence Regression: A Model for ...

The paper shows the trade-offs between interpretability, computation cost and accuracy of many algorithms for fraud detection from machine learning perspective which provides important clues in this ...

⭐ If you like this, please give the repo a star – it helps! Check our demo on Colab The fully-open successor to Google DeepMind’s AlphaEvolve for automated algorithm discovery. First released 📅 Nov ...