Papers

• A Mathematical Introduction to Diffusion Models (2026)
  Jianfeng Lu
  4.39
• The Seriality Gap in Video Diffusion Models (2026)
  Jorge Diaz Chao et al.
  4.39
• Non-monotonic diffusion from nonequilibrium driving (2026)
  Manish Patel et al.
  3.51
• Diffusion-Guided Renormalization of Neural Systems via Tensor Networks (2025)
  Nathan X. Kodama
  1.50
• A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions (2025)
  Toan Huynh et al.
  1.39
• Shape optimization of metastable states (2025)
  No\'e Blassel and Tony Leli\`evre and Gabriel Stoltz
  1.33
• Optimal multi-time-scale estimates for diluted autocatalytic chemical networks. (1) Introduction and $\sigma^*$-dominant case (2025)
  Jeremie Unterberger
  1.06
• A Riemannian Stochastic Representation for Quantifying Model Uncertainties in Molecular Dynamics Simulations (2022)
  Hao Zhang and Johann Guilleminot
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• Stochastic PDE representation of random fields for large-scale Gaussian process regression and statistical finite element analysis (2023)
  Kim Jie Koh and Fehmi Cirak
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• Directional diffusion models for graph representation learning (2023)
  Run Yang et al.
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• Diffusive Gibbs Sampling (2024)
  Wenlin Chen et al.
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• Stochastic approach for elliptic problems in perforated domains (2024)
  Jihun Han et al.
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• Diffusion Model-based Parameter Estimation in Dynamic Power Systems (2024)
  Feiqin Zhu et al.
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