#Generative Modeling

Articles (4)

• 🇺🇸 Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences — 12/03/2026 [USA]

  arXiv:2603.10592v1 Announce Type: cross Abstract: We reveal a precise mathematical framework about a new family of generative models which we call Gradient Flow Drifting. With this framework, we prov...

  Related: #Machine Learning
• 🇺🇸 Universal Fine-Grained Symmetry Inference and Enforcement for Rigorous Crystal Structure Prediction — 20/02/2026 [USA]

  arXiv:2602.17176v1 Announce Type: cross Abstract: Crystal structure prediction (CSP), which aims to predict the three-dimensional atomic arrangement of a crystal from its composition, is central to m...

  Related: #Materials Science, #Artificial Intelligence, #Computational Physics, #Crystallography
• 🇺🇸 GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning — 19/02/2026 [USA]

  arXiv:2507.03267v2 Announce Type: replace Abstract: Dynamic Text-Attributed Graphs (DyTAGs), which intricately integrate structural, temporal, and textual attributes, are crucial for modeling complex...

  Related: #Graph Neural Networks, #Dynamic Graphs, #Text‑Attributed Graphs, #Benchmark Development
• 🇺🇸 Token-Based Audio Inpainting via Discrete Diffusion — 18/02/2026 [USA]

  arXiv:2507.08333v4 Announce Type: replace-cross Abstract: Audio inpainting seeks to restore missing segments in degraded recordings. Previous diffusion-based methods exhibit impaired performance when...

  Related: #Audio Restoration, #Diffusion Models, #Tokenization, #Machine Learning