Fresh picks from ArXiv
This week on ArXiv: class-dependent generative models, label-feature propagations, and space-time GNNs 🚀

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

Biology
* Pre-training Molecular Graph Representation with 3D Geometry
* Molecular Graph Generation via Geometric Scattering
* Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design with Regina Barzilay and Tommi Jaakkola
* CCGG: A Deep Autoregressive Model for Class-Conditional Graph Generation

GNNs
* Graph Neural Networks with Learnable Structural and Positional Representations with Yoshua Bengio and Xavier Bresson
* ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network with Philip S. Yu
* Training Stable Graph Neural Networks Through Constrained Learning with Alejandro Ribeiro
* Space-Time Graph Neural Networks with Alejandro Ribeiro
* Equivariant Subgraph Aggregation Networks with Michael M. Bronstein and Haggai Maron

KG
* A Survey on State-of-the-art Techniques for Knowledge Graphs Construction and Challenges ahead

LP
* Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs
* Why Propagate Alone? Parallel Use of Labels and Features on Graphs
* Label Propagation across Graphs: Node Classification using Graph Neural Tangent Kernels