Papers

• Bayesian Graph Traversal (2025)
  William N. Caballero et al.
  1.06
• Hard negative sampling in hyperedge prediction (2025)
  Zhenyu Deng et al.
  1.06
• Directed Hybrid Random Networks Mixing Preferential Attachment with Uniform Attachment Mechanisms (2021)
  Tiandong Wang and Panpan Zhang
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• Conditions and Assumptions for Constraint-based Causal Structure Learning (2021)
  Kayvan Sadeghi and Terry Soo
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• Evolving-Graph Gaussian Processes (2021)
  David Blanco-Mulero et al.
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• Extending compositional data analysis from a graph signal processing perspective (2022)
  Christopher Rieser and Peter Filzmoser
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• Stability of Entropic Wasserstein Barycenters and application to random geometric graphs (2022)
  Marc Theveneau et al.
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• Edgewise outliers of network indexed signals (2023)
  Christopher Rieser and Anne Ruiz-Gazen and Christine Thomas-Agnan
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• Stochastic Degree Sequence Model with Edge Constraints (SDSM-EC) for Backbone Extraction (2023)
  Zachary P. Neal and Jennifer Watling Neal
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• Structural restrictions in local causal discovery: identifying direct causes of a target variable (2023)
  Juraj Bodik et al.
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• Model-Based Inference and Experimental Design for Interference Using Partial Network Data (2024)
  Steven Wilkins Reeves et al.
  —