Papers

• Combining complex Langevin dynamics with score-based and energy-based diffusion models (2025)
  Gert Aarts et al.
  3.04
• On learning higher-order cumulants in diffusion models (2024)
  Gert Aarts et al.
  2.49
• Diffusion model for SU(N) gauge theories (2026)
  Javad Komijani et al.
  1.83
• Noise scheduling and linear dynamics in diffusion models on Lie groups (2026)
  Javad Komijani
  1.83
• Analytic Bijections for Smooth and Interpretable Normalizing Flows (2026)
  Mathis Gerdes et al.
  1.61
• Toward Scalable Normalizing Flows for the Hubbard Model (2026)
  Janik Kreit et al.
  1.61
• SCORENF: Score-based Normalizing Flows for Sampling Unnormalized distributions (2025)
  Vikas Kanaujia et al.
  1.44
• Group-Equivariant Diffusion Models for Lattice Field Theory (2025)
  Octavio Vega et al.
  1.44
• SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows (2025)
  Janik Kreit et al.
  1.17
• Physics-Conditioned Diffusion Models for Lattice Gauge Theory (2025)
  Qianteng Zhu et al.
  1.00
• Simulating the Hubbard Model with Equivariant Normalizing Flows (2025)
  Dominic Schuh et al.
  0.94
• Normalizing flows for SU($N$) gauge theories employing singular value decomposition (2025)
  Javad Komijani et al.
  0.94
• Applications of flow models to the generation of correlated lattice QCD ensembles (2024)
  Ryan Abbott et al.
  —
• Practical applications of machine-learned flows on gauge fields (2024)
  Ryan Abbott et al.
  —
• Numerical determination of the width and shape of the effective string using Stochastic Normalizing Flows (2024)
  Michele Caselle et al.
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• Diffusion models learn distributions generated by complex Langevin dynamics (2024)
  Diaa E. Habibi et al.
  —