Papers

• A user's guide to PINNs in geometric analysis: lessons from the asymptotic Plateau problem (2026)
  Tancredi Schettini Gherardini
  1.94
• Score Shocks: The Burgers Equation Structure of Diffusion Generative Models (2026)
  Krisanu Sarkar
  1.78
• Constructive conditional normalizing flows (2026)
  Borjan Geshkovski and Dom\`enec Ruiz-Balet
  1.67
• Backward Reconstruction of the Chafee--Infante Equation via Physics-Informed WGAN-GP (2026)
  Joseph L. Shomberg
  1.61
• PILD: Physics-Informed Learning via Diffusion (2026)
  Tianyi Zeng et al.
  1.61
• A PDE Perspective on Generative Diffusion Models (2025)
  Kang Liu and Enrique Zuazua
  1.50
• Adapting Noise to Data: Generative Flows from 1D Processes (2025)
  Jannis Chemseddine et al.
  1.44
• Moment Estimate and Variational Approach for Learning Generalized Diffusion with Non-gradient Structures (2025)
  Fanze Kong et al.
  1.33
• A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions (2025)
  Nishant Jain et al.
  1.33
• An explicit formulation of the learned noise predictor $\epsilon_{\theta}({\bf x}_t, t)$ via the forward-process noise $\epsilon_{t}$ in denoising diffusion probabilistic models (DDPMs) (2025)
  KiHyun Yun
  1.28
• Multi-Step Consistency Models: Fast Generation with Theoretical Guarantees (2025)
  Nishant Jain et al.
  1.17
• Wasserstein Bounds for generative diffusion models with Gaussian tail targets (2024)
  Xixian Wang et al.
  1.00
• Denoising Diffusion Restoration Tackles Forward and Inverse Problems for the Laplace Operator (2024)
  Amartya Mukherjee et al.
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• Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation (2024)
  Noboru Isobe et al.
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• Transformer-based Koopman Autoencoder for Linearizing Fisher's Equation (2024)
  Kanav Singh Rana et al.
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