Fresh Picks from Arxiv
The past week on GraphML arXiv: Dynamics, generalization and structure-aware generation for molecules, learning graph combinatorial optimization, and more.

⚛️ Molecular Graphs:
- How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations? ft. Johannes Gasteiger, Stephan Gunnemann.
- How Do Graph Networks Generalize to Large and Diverse Molecular Systems? ft. Johannes Gasteiger, Stephan Gunnemann, Open Catalyst Project Team.
- In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation

💼 Graph Combinatorial Optimization:
- Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
- Learning-Based Approaches for Graph Problems: A Survey

🌐 Miscellaneous:
- Graph-based Approximate NN Search: A Revisit
- Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
- C3KG: A Chinese Commonsense Conversation Knowledge Graph
- Graph Neural Networks Designed for Different Graph Types: A Survey
- Equilibrium Aggregation: Encoding Sets via Optimization ft. Fabian Fuchs.

(If I forgot to mention your paper, please shoot me a message and I will update the post.)