Constrained Goal-directed Planar Graph Generation with Grammar-based Reinforcement Learning
cs.LG
Submitted: 2026-10-05
Updated: 2026-10-05
Code: https://github.com/ETHZ-EDAC/constrained-graph-rl
Terminology
Sources
- Generative Diffusion Models on Graphs: Methods and Applications
- Generative Modelling of Structurally Constrained Graphs
- Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance
- GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
- Optimization of Molecules via Deep Reinforcement Learning
- Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
- Proximal Policy Optimization Algorithms
- Spherical Message Passing for 3D Graph Networks
- Directional Message Passing for Molecular Graphs
- E(n) Equivariant Graph Neural Networks
- Representation Learning on Graphs with Jumping Knowledge Networks
- Graph Matching Networks for Learning the Similarity of Graph Structured Objects
- Variational Inference with Normalizing Flows
- Safe Exploration in Continuous Action Spaces
- Guided Graph Generation: Evaluation of Graph Generators in Terms of Network Statistics, and a New Algorithm
- Efficient and Scalable Graph Generation through Iterative Local Expansion
- DiGress: Discrete Denoising diffusion for graph generation
- Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
- MUDiff: Unified Diffusion for Complete Molecule Generation
- Goal-directed graph construction using reinforcement learning
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