Preprint Open access
Optimization Encoders: Rethinking Second-Order Meta-Learning for Neural Fields
Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred from observed data. In meta-learning, this encoding occurs through gradient updates induced by the decoder, tying representation learning directly to decoder design. We fo …