Authors

Yam Eitan

Publications 2

Preprint Open access

CrossGMN: Graph Metanetworks for Cross-Architecture Weight-Space Transformations

Adir Dayan, Yam Eitan, Haggai Maron · 2026

Weight-space networks operate directly on parameters of other neural networks, enabling tasks such as predicting model properties, editing trained models, and generating weights. Weight-space symmetries such as neuron permutations make equivariance a key design principle. However, existing equivariant weight-space arch …

Preprint Open access

Transferable Graph Metanetworks

Yuxin Ma, Adir Dayan, Yam Eitan et al. · 2026

A weight space network (or metanetwork) takes the weights of another neural network as input and predicts properties of it. Most prior work trains such models on input networks of one or a few fixed sizes and evaluates them in-distribution. The few attempts at out-of-distribution size generalization remain limited in s …

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