Modelling Multivariate Ranking Functions with Min-Sum Networks. - Xiaoting Shao; Zhongjie Yu 001; Arseny Skryagin; Tjitze Rienstra; Matthias Thimm; Kristian Kersting (SUM, 2020)

Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. - Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (AAAI, 2021)

Leveraging probabilistic circuits for nonparametric multi-output regression. - Zhongjie Yu 001; Mingye Zhu; Martin Trapp 001; Arseny Skryagin; Kristian Kersting (UAI, 2021)

SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming. - Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

Neural-Probabilistic Answer Set Programming. - Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (KR, 2022)

Scalable Neural-Probabilistic Answer Set Programming. - Arseny Skryagin; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (J. Artif. Intell. Res., 2023)

Graph Neural Networks Need Cluster-Normalize-Activate Modules. - Arseny Skryagin; Felix Divo; Mohammad Amin Ali; Devendra Singh Dhami; Kristian Kersting (NeurIPS, 2024)

Answer Set Networks: Casting Answer Set Programming into Deep Learning. - Arseny Skryagin; Daniel Ochs; Phillip Deibert; Simon Kohaut; Devendra Singh Dhami; Kristian Kersting (CoRR, 2024)