5 papers
RAISE: LLM-based Automated Heuristic Design with Robust Adversary Instance Search
Fei Liu, Alessio Figalli, Patrick Owen +1
Automated Heuristic Design (AHD) with Large Language Models (LLMs) has shown remarkable progress in discovering high-quality heuristics. However, existing LLM-based AHD methods opt…
Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
Olivia Jullian Parra, Sara Zoccheddu, David Catalan Cerezo +7
Target trial emulation (TTE) enables causal questions to be studied with observational data when randomized controlled trials (RCTs) are infeasible. Yet treatment-effect methods of…
Towards replacing detector simulation with heterogeneous GNNs in flavour physics analyses
Guillermo Hijano, Davide Lancierini, Alexander Mclean Marshall +8
Driven by the increasing volume of recorded data, the demand for simulation from experiments based at the Large Hadron Collider will rise sharply in the coming years. Addressing th…
Large Language Models for Physics Instrument Design
Sara Zoccheddu, Shah Rukh Qasim, Patrick Owen +1
We study the use of large language models (LLMs) for physics instrument design and compare their performance to reinforcement learning (RL). Using only prompting, LLMs are given ta…
Ultra-Fast Muon Transport via Histogram Sampling on GPUs
Luis Felipe P. Cattelan, Shah Rukh Qasim, Patrick H. Owen +1
We present a GPU-accelerated method for muon transport based on histogram sampling that delivers orders of magnitude faster performance than CPU-based Geant4 simulation. Our method…