Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

arXiv:2608.06276 · stat.ML, cs.LG, math.AT · Submitted 2026-08-06 · Read on arXiv

Farzana Nasrin

stat.ML, cs.LG, math.AT

Submitted: 2026-08-06

Comments: 27 pages, 7 figures, and 5 tables

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

Terminology

• Reinforcement Learning — 12× in this paper · explained in 4 episodes
• Stochastic Dynamics — 12× in this paper · explained in 3 episodes
• Generator — 9× in this paper · explained in 2 episodes
• Fidelity — 8× in this paper · explained in 2 episodes
• Wasserstein Distance — 8× in this paper · explained in 6 episodes
• Regularization — 7× in this paper · explained in 3 episodes
• Persistent Homology — 6× in this paper · explained in 4 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Actor — 3× in this paper · explained in 3 episodes
• Distribution Matching — 2× in this paper · explained in 4 episodes
• International Conference on Machine Learning — 2× in this paper
• Point Clouds — 2× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 26 episodes
• Reward Function — 2× in this paper · explained in 4 episodes
• Reward Shaping — 2× in this paper · explained in 2 episodes
• Vietoris Rips — 2× in this paper
• Adam — 1× in this paper · explained in 3 episodes
• Autism Brain Imaging Data Exchange — 1× in this paper
• Bayesian Framework — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 3 episodes
• Distance Preservation — 1× in this paper · explained in 2 episodes
• Editor — 1× in this paper · explained in 2 episodes
• Entropy Regularization — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Maximum Mean Discrepancy (MMD) — 1× in this paper · explained in 3 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Parameterization — 1× in this paper · explained in 2 episodes
• Point Cloud Data — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 6 episodes
• Topological Data Analysis (TDA) — 1× in this paper · explained in 3 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

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