Learning Shortest Paths with Generative Flow Networks
Learning Shortest Paths with Generative Flow Networks explores Develop a graph pathfinding tool using Generative Flow Networks for efficient shortest path computation.. Commercial viability score: 4/10 in Graph Pathfinding.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisTransport, Don't Generate: Deterministic Geometric Flows for Combinatorial OptimizationViability: 3.0
- Builds On ThisHierarchical Discrete Flow Matching for Graph GenerationViability: 3.0
- Higher ViabilityWINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault AdaptationViability: 6.0
- Higher ViabilityControlling Exploration-Exploitation in GFlowNets via Markov Chain PerspectivesViability: 5.0
- Higher ViabilityFlowette: Flow Matching with Graphette Priors for Graph Generation