Gravitational Waves

可解释 AI 与强化学习协同驱动的引力波数据处理新方法探索

第一届空间引力波科学数据分析研讨会会议

Automated Algorithmic Discovery for Scientific Computing through LLM-Guided Evolutionary Search: A Case Study in Gravitational-Wave Detection

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.

Evo-MCTS: Evolutionary Monte Carlo Tree Search for Gravitational Wave Detection

🧬 Revolutionary LLM-guided framework for automated algorithmic discovery in gravitational wave detection. Combines evolutionary optimization with Monte Carlo Tree Search to achieve 20.2% improvement over domain-specific methods and 59.1% over LLM-based optimization frameworks on MLGWSC-1 benchmark.

Recent Advances in Simulation-based Inference for Gravitational Wave Data Analysis

A review of modern simulation-based inference techniques for gravitational wave data analysis, highlighting methodological advances, practical applications, and future outlook.

引力波数据处理与人工智能技术应用

学术访问

Interpretable Gravitational Wave Data Analysis with Deep Learning and Large Language Models

学术访问

Interpretable Gravitational Wave Data Analysis with Deep Learning and Large Language Models

The 12th KAGRA international workshop (KIW-12)

Interpretable Gravitational Wave Data Analysis with Deep Learning and Large Language Models

BIMSA Workshop on Gravitational Wave Astronomy

Towards Transparent AI in Gravitational Wave Data Analysis: Methods, Limitations, and New Directions

2025昆明引力年会

Deep Learning Applications in Gravitational Wave Data Analysis: From Discovery to Characterization

PKU-KIAA 访问研讨会