Energy-based models have the natural advantage of flexibility in the form of the energy function. Recently, energy-based models have achieved great success in modeling high-dimensional data in computer vision and natural language processing. In accordance with these signs of progress, we build a versatile energy-based model for High Energy Physics events at the Large Hadron Collider. This framework builds on a powerful generative model and describes higher-order inter-particle interactions. It suits different encoding architectures and builds on implicit generation. As for applicational aspects, it can serve as a powerful parameterized event generator, a generic anomalous signal detector, and an augmented event classifier.

翻译：能量模型在能量函数形式上具有天然灵活性优势。近年来，能量模型在计算机视觉和自然语言处理的高维数据建模领域取得了显著成功。紧跟上述进展，我们为大强子对撞机高能物理事件构建了一个普适性能量模型。该框架基于强大的生成模型，能够描述高阶粒子间相互作用，兼容不同编码架构，并依托隐式生成方法建立。在应用层面，该模型可充当高效的参数化事件生成器、通用异常信号检测器以及增强型事件分类器。