garch, garch, time series models
Generalized AutoRegressive Conditional Heteroskedasticity models time-varying volatility in financial time series.
9,967 technical terms and definitions
Generalized AutoRegressive Conditional Heteroskedasticity models time-varying volatility in financial time series.
Use gas adsorption isotherms.
Gas cabinets safely house compressed gas cylinders with monitoring and shutoff.
Enclosed ventilated cabinet for storing toxic or hazardous gas cylinders.
Gas distribution systems route specialty gases from storage to process tools.
Multi-head attention in GAT computes multiple attention mechanisms in parallel stabilizing learning and improving expressiveness.
Graph Attention Networks compute node representations by applying self-attention to neighborhood aggregation with learned attention coefficients.
Gate dielectric interface quality affects mobility threshold voltage and reliability requiring careful engineering.
Thin high-quality oxide under transistor gate critical for performance.
Remove dummy gate and fill with real gate.
Gate stacks consist of gate dielectric and gate electrode layers whose materials thickness and interfaces determine transistor electrical characteristics.
Leakage through gate dielectric.
Next-gen transistor with gate surrounding channel.
Gate-first processes deposit gate stack before source-drain formation simplifying but limiting thermal budget.
Form metal gate before source/drain.
Impact on overall process flow.
Form gate after high-temperature processing.
Gate-last processes form gate after source-drain using replacement gate enabling high-k metal gate compatibility.
Entry point to cavity.
Gated convolutions use multiplicative gates controlling information flow.
Test structure for junction characterization.
Use gates to control information flow.
Combine linear transform with gating.
Convolutional networks with gating.
Efficient feature aggregation.
Use gates to control information flow.
Decides which experts to activate for each input.
Decide which paths to activate.
Respect gauge symmetries.
Kernel-based force field.
Shape and orientation of Gaussians.
Model process with uncertainty quantification.
Optimize Gaussian parameters.
Represent scenes as 3D Gaussians.
Gaussian splatting represents scenes as collections of 3D Gaussians for real-time differentiable rendering.
Graph Contextualized Self-Attention combines graph neural networks with self-attention for modeling both local and global session context.
Global Context Enhanced Graph Neural Networks combine local session and global preference modeling.
Spectral graph convolutional networks define convolutions through graph Laplacian eigendecomposition.
Graph Convolutional Policy Network generates graphs through reinforcement learning with domain-specific rewards for molecular design.
Gradient-based architecture search with differentiable sampling enables efficient single-path supernet training.
GDPR/CCPA require consent, data minimization, right to deletion. Design AI systems with privacy by default.
Standard design data format.
Generalized End-to-End loss trains speaker embeddings by optimizing similarity within and between speakers.
Use class-conditional language models for control.
GELU-gated linear unit.
Smooth activation used in Transformers.
GELU and SwiGLU are activation functions in transformers. SwiGLU used in modern LLMs like Llama.
SECS/GEM standard for 300mm fabs.
Robust loss for outliers.
Gemba walks involve management observing processes directly where work happens.