Papers

• Graph Laplacians, Riemannian Manifolds and their Machine-Learning (2020)
  Yang-Hui He et al.
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• An algebraic approach to product-form stationary distributions for some reaction networks (2020)
  Beatriz Pascual-Escudero and Linard Hoessly
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• Algebraic Model Selection and Experimental Design in Biological Data Science (2021)
  Anyu Zhang et al.
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• Cluster Algebras: Network Science and Machine Learning (2022)
  Pierre-Philippe Dechant et al.
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• Combinatorial and algebraic perspectives on the marginal independence structure of Bayesian networks (2022)
  Danai Deligeorgaki et al.
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• Function Space and Critical Points of Linear Convolutional Networks (2023)
  Kathl\'en Kohn et al.
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• Identifiability of Product of Experts Models (2023)
  Spencer L. Gordon et al.
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