non-default rules (ndr),non-default rules,ndr,design
Custom design rules for critical nets.
9,967 technical terms and definitions
Custom design rules for critical nets.
Quantum transport simulation method.
Compute long-range dependencies.
Handle non-Gaussian distributions.
Non-parametric tests make minimal distribution assumptions for robust inference.
Solder doesn't wet surface.
Parts not meeting specifications.
Distribution-free methods.
Nonparametric Hawkes processes learn excitation kernels from data without assuming parametric forms.
Predict surface normals from images.
Condition on surface normals.
Verify data follows normal distribution.
Normalize features: min-max, z-score. Many algorithms need scaling.
Ranking quality metric.
Normalized yield adjusts for process complexity enabling fair comparison across products.
Invertible transformations for density estimation.
Wafer orientation markers.
Notch orientation establishes coordinate system reference for wafer positioning and mapping.
Undercut at bottom of feature due to charge buildup.
I can help you structure notebooks for clean experiments: sections, logging, seeding, and export of results.
Nous Hermes is Nous Research model. Strong general capabilities.
Render from unseen viewpoints.
Generate views from new camera positions.
Help authors write books.
Assess if invention is novel.
Novelty search optimizes for behavioral novelty rather than objective rewards discovering diverse solutions in deceptive environments.
Normalize gradients by layer.
Choose proper pickup tool.
Number defective.
Dedicated chip for neural network inference.
NPUs are neural processing units in phones/laptops. Hardware acceleration for on-device inference.
Net Present Value discounts future cash flows to evaluate investment decisions.
One-time costs for design masks and setup.
Non-Recurring Engineering costs cover design development and mask tooling.
Non-dominated Sorting Genetic Algorithm II is a multi-objective evolutionary algorithm commonly used for Pareto-optimal architecture discovery in NAS.
NSGA-Net applies multi-objective evolutionary algorithm to discover Pareto-optimal neural architectures.
Theoretical framework for understanding deep learning.
Neural Tangent Kernel-based scaling.
Scale positional embeddings for longer context.
Detect light elements like hydrogen.
Formation of precipitate nuclei.
Nucleus sampling threshold controls diversity by probability mass cutoff.
Top-p (nucleus) sampling picks from smallest set covering probability p. Dynamic vocabulary size.
Nuisance defects are detected anomalies that don't cause yield loss requiring filter optimization.
Detected defects that don't affect yield.
Null-text inversion optimizes unconditional embeddings for accurate real image editing.
Find embeddings for specific images.
Sampling iterations tradeoff.
Test numerical reasoning.
Measure of lens light-gathering ability affects resolution.