Preprint reports privacy-preserving cell analysis close to standard accuracy
A three-party secure-computing system came close to CellCnn on small CMV/NK and AML benchmarks, but its protections depend on a non-colluding, honest-majority setup.
141–160
A three-party secure-computing system came close to CellCnn on small CMV/NK and AML benchmarks, but its protections depend on a non-colluding, honest-majority setup.
A controlled comparison found no significant advantage for the immersive system on errors, recall, confidence, usability or reported workload.
A mathematical framework uses summary information about a system’s starting state to bound the chance of entering an unsafe region over a fixed time horizon.
A theoretical study finds conditional local stability for key Iwasawa invariants, while its p-adic L-function result depends on the cyclotomic Main Conjecture.
Nested sampling methods recorded higher reported toxicity rates and lower perplexity than listed baselines, but the test used one model and automated proxy measures.
A symmetry-based design split modeled power between two patterns while holding a third near the numerical floor.
RMWorld recorded lower scores than named baselines in a 100-trial formula-channel test and a 30-seed severe-load comparison, but used more offline computation.
The final version posted the lowest reported lane error and greatest curve exposure, but the evaluation did not measure real-world driving or numerical collision rates.
A descriptive analysis of ViT-Tiny training found rare movement toward deeper layers and earlier stabilization in the network’s deeper sections.
A computational study found that one measure tracked half-system entanglement and marked three mean-field phase boundaries, while finer signals depended on window shape.
In a four-level excitonic dimer, SAKE closely matched an exact projected calculation and recovered three synthetic control targets; tests on larger systems or measured data are still absent.
The theoretical scheme uses quantum amplitude amplification to target large fixed-photon states, but no laboratory result is reported.
An archival reading places one manuscript between January 22 and April 5 and suggests it was likely being prepared for a Ferienkurs lecture, while leaving its exact setting uncertain.
A fully relativistic classical calculation finds no spontaneous velocity-dependent drag during uniform motion, while a nonrelativistic version produces terms the authors interpret as artifacts.
In computer benchmarks, the reinforcement-learning policy had lower reported errors than conventional and adaptive baselines; quantum-hardware performance was not validated.
Simulations suggest that changing the focus velocity could produce parabolic or conical near-field patterns, but no experiment is reported.
Galactic masking alone left a strong mismatch, but combining it with empirical survey-selection maps brought the observed profile into line with isotropic mock skies—while leaving a key modeling caveat.
The framework measures the volume of pure states compatible with a preparation, but broader entropy properties remain unresolved.
The system combines vision-language guidance with low-level visual priors and reports an average 31.00 dB PSNR and 0.923 SSIM in its expanded comparison.
A theorem-based analysis also maps where entropy values can accumulate and identifies the geometry behind the largest value below 1.