Xiaoting Shao

Publication Activity (10 Years)

Years Active: 2019-2022
Publications (10 Years): 14

Top Topics

Probabilistic Model

Abstract Argumentation

Top Venues

Datenbank-Spektrum

Int. J. Approx. Reason.

Nat. Mach. Intell.

Publications

Xiaoting Shao, Karl Stelzner, Kristian Kersting
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement. CoRR (2022)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140 (2022)
Xiaoting Shao, Kristian Kersting
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models. CoRR (2022)
Xiaoting Shao, Arseny Skryagin, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. AAAI (2021)
Xiaoting Shao, Tjitze Rienstra, Matthias Thimm, Kristian Kersting
Towards Understanding and Arguing with Classifiers: Recent Progress. Datenbank-Spektrum 20 (2) (2020)
Tjitze Rienstra, Matthias Thimm, Kristian Kersting, Xiaoting Shao
Independence and D-separation in Abstract Argumentation. KR (2020)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM (2020)
Xiaoting Shao, Zhongjie Yu, Arseny Skryagin, Tjitze Rienstra, Matthias Thimm, Kristian Kersting
Modelling Multivariate Ranking Functions with Min-Sum Networks. SUM (2020)
Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting
Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations. CoRR (2020)
Patrick Schramowski, Wolfgang Stammer, Stefano Teso, Anna Brugger, Franziska Herbert, Xiaoting Shao, Hans-Georg Luigs, Anne-Katrin Mahlein, Kristian Kersting
Making deep neural networks right for the right scientific reasons by interacting with their explanations. Nat. Mach. Intell. 2 (8) (2020)
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI (2019)
Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni
Neural-Symbolic Argumentation Mining: an Argument in Favour of Deep Learning and Reasoning. CoRR (2019)
Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR (2019)
Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni
Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning. Frontiers Big Data 2 (2019)