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cs.LG2026
Derivative-Informed Training of Neural Operators On-the-Fly via Sketched Tangent Consistency
Xinhan Yang, Lu Lu, Shancong Mou
Derivative-informed training improves neural operators by directly supervising their input-output sensitivities, which is crucial when neural operators are used as differentiable s…
cs.LG2026
Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
Deyi Kong, Zaiwei Chen, Shuzhong Zhang +1
In this work, we propose Natural Hypergradient Descent (NHGD), a new method for solving bilevel optimization problems. To address the computational bottleneck in hypergradient esti…