Papers

• Diffusion-Network Alignment: An Efficient Algorithm and Explicit Probability Bounds (2026)
  Ziao Wang et al.
  1.89
• The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives (2026)
  Ankur Moitra et al.
  1.83
• Query Lower Bounds for Diffusion Sampling (2026)
  Zhiyang Xun et al.
  1.78
• Graph Neural Network-Informed Predictive Flows for Faster Ford-Fulkerson and PAC-Learnability (2026)
  Eleanor Wiesler et al.
  1.78
• Steering diffusion models with quadratic rewards: a fine-grained analysis (2026)
  Ankur Moitra et al.
  1.67
• Parallel Sampling via Autospeculation (2025)
  Nima Anari et al.
  1.50
• Posterior Sampling by Combining Diffusion Models with Annealed Langevin Dynamics (2025)
  Zhiyang Xun et al.
  1.44
• Efficient Diffusion Models for Symmetric Manifolds (2025)
  Oren Mangoubi et al.
  1.17
• DDPM Score Matching and Distribution Learning (2025)
  Sinho Chewi and Alkis Kalavasis and Anay Mehrotra and Omar Montasser
  1.11
• Diffusion Map Autoencoder (2024)
  Julio Candanedo
  0.83
• Learning Mixtures of Gaussians Using Diffusion Models (2024)
  Khashayar Gatmiry et al.
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• In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies (2024)
  Yunbum Kook et al.
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• Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel (2024)
  Shivam Gupta et al.
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• Parallel Simulation for Log-concave Sampling and Score-based Diffusion Models (2024)
  Huanjian Zhou and Masashi Sugiyama
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