Importance-weighted least squares (IWLS) is widely used to correct covariate shift in unsupervised domain adaptation, yet most prior work assumes that an appropriate source dataset…
Biased-noise threshold claims for surface-code families are often expressed in terms of the nominal hardware dephasing ratio $\eta$, yet realistic gate decompositions, measurement…
This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts. This study explores automated research pipelines with rigo…
Type 1 diabetes (T1D) remains a paradigmatic autoimmune disease in which loss of beta-cell function causes dysglycemia, severe hypoglycemia, and lifelong dependence on exogenous in…
We develop a proof program that targets a quantitative bridge between scale-invariant local energy control and global critical $L^\infty_t L^3_x$ bounds for the three-dimensional i…
We study 3D incompressible Navier--Stokes flow on a periodic box and design a diagnostic suite that links classical Prodi--Serrin mixed norms, weak-$L^p$ (Lorentz) proxies, scaling…
We study conservative offline reinforcement learning with uncertainty-aware policy improvement under a tight compute budget. The goal is to combine conservative value regularizatio…
This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts. This study explores automated research pipelines with rigo…
