DeepMind & Stanford U’s UNFs: Advancing Weight-Space Modeling with Universal Neural Functionals

A research team from Google DeepMind and Stanford University introduces a groundbreaking algorithm known as universal neural functionals (UNFs), which autonomously constructs permutation-equivariant models for any weight space, offering a versatile solution to the architectural constraints encountered in prior works.

ai algorithm artificial intelligence constraints deepmind deep-neural-networks google google deepmind groundbreaking machine learning machine learning & data science ml modeling neural function prior research research team solution space stanford stanford university team technology university