Training Infinitely Deep and Wide Transformers

In three linesTheoretical paper on transformer training in mean-field regime (infinite depth and width). Authors model training as controlling a neural PDE (vs ODE for ResNets), establish well-posedness of forward pass, derive explicit formulas for Wasserstein gradients, and prove gradient flow convergence to global minima under NTK injectivity conditions.

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