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Haggai Maron
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A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening
Fast Encoder-Based 3D from Casual Videos via Point Track Processing
GRANOLA: Adaptive Normalization for Graph Neural Networks
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
Equivariant Deep Weight Space Alignment
Future Directions in Foundations of Graph Machine Learning
Improved Generalization of Weight Space Networks via Augmentationss
On the Expressive Power of Spectral Invariant Graph Neural Networks
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Efficient Subgraph GNNs by Learning Effective Selection Policies
Graph Metanetworks for Processing Diverse Neural Architectures
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Norm-guided latent space exploration for text-to-image generation
Equivariant Architectures for Learning in Deep Weight Spaces
Equivariant Polynomials for Graph Neural Networks
Graph Positional Encoding via Random Feature Propagation
A Simple and Universal Rotation Equivariant Point-cloud Network
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries
Equivariant Subgraph Aggregation Networks
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Multi-Task Learning as a Bargaining Game
Optimizing Tensor Network Contraction Using Reinforcement Learning
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
From Local Structures to Size Generalization in Graph Neural Networks
How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Auxiliary Learning by Implicit Differentiation
Self-Supervised Learning for Domain Adaptation on Point-Clouds
On the Universality of Rotation Equivariant Point Cloud Networks
On Learning Sets of Symmetric Elements
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