🧬 Revolutionary LLM-guided framework for automated algorithmic discovery in gravitational wave detection. Combines evolutionary optimization with Monte Carlo Tree Search to systematically explore algorithm spaces and achieve 20.2% improvement over state-of-the-art methods on MLGWSC-1 benchmark.
A framework for automated discovery of gravitational-wave detection algorithms, combining LLM guidance with Evolutionary Monte Carlo Tree Search, enabling efficient and creative pipeline discovery.
A review of modern simulation-based inference techniques for gravitational wave data analysis, highlighting methodological advances, practical applications, and future outlook.