TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching

arXiv:2607.16894 · cs.LG · Submitted 2026-07-18 · Read on arXiv

cs.LG

Submitted: 2026-07-18

Updated: 2026-09-18

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Flow Matching — 37× in this paper · explained in 7 episodes
• Transformer — 13× in this paper · explained in 2 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Generative Model — 8× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Generative Modeling — 5× in this paper · explained in 3 episodes
• Sparsity — 5× in this paper · explained in 4 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Normalizing Flows — 2× in this paper · explained in 4 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Diffusion Processes — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Knowledge Discovery and Data Mining — 1× in this paper
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Time Series Forecasting — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Flow Matching Guide and Code
• Let EEG Models Learn EEG
• Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
• SPD Matrix Learning for Neuroimaging Analysis: Perspectives, Methods, and Challenges
• Graph Generation with Spectral Geodesic Flow Matching
• Scalable Generative Modeling of Weighted Graphs

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