Automated Algorithm Selection with Hyperparameter Optimization

MachSMT: An ML-Driven Algorithm Selection tool for SMT Solvers

ASF is a flexible Python library for algorithm selection

Sparkle is a Programming by Optimisation (PbO)-based problem-solving platform designed to enable the widespread and effective use of PbO techniques for improving the state-of-the-art in solving a broad range of prominent AI problems, including SAT and AI Planning.

Mosaic: MCTS-based Pipeline Optimization

An AutoRecSys Library built around LensKit. Performs automatic algorithm selection, hyperparameter optimzation and ensembling on LensKit models.

Local Streamlit app that suggests and ranks ML, AI, NLP, computer vision, time series, anomaly detection, document intelligence, GenAI, and RAG algorithms for a project.

Pattern-Aware Complexity Framework (PACF) - A Python implementation for analyzing and exploiting structural patterns in NP-hard optimization problems, with a focus on the Traveling Salesman Problem (TSP). Supports extensible domains like genetic sequences and weather forecasting. Licensed under MIT

Stochastic search based CASH optimizer

Algorithm Selection platform for Object Detection

Phase-adaptive SAT solver using LLM-based clause density prediction to route between resolution, spectral, and hybrid algorithms. Achieves 1.4-2x speedup on phase transition instances. Synthesized via Synth-Fuse autonomous algorithm generation.

One-page A4 cheat sheet mapping problem clues to algorithms, generated from an editable YAML decision flow.

Code and data for "The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation" (ICML 2026)

ML-driven meta-system that predicts the optimal graph search algorithm (BFS, DFS, A*) for a maze using structural features and regret evaluation.