29,259 technical terms and definitions
discrete mathematics graphs, vertices and edges, graph traversal, graph connectivity, shortest path algorithms, graph coloring, network flow, graph theory semiconductor
Graph theory studies systems by separating the things that exist from the relationships that connect them. A graph can represent nets joined by components, process steps…
Graph Theory, Network Flow, and Spectral Laplacians 1. Networks as mathematical objects A graph represents objects and pairwise relationships. The objects are vertices and…
Graph-Based Time Series Models Introduction & Motivation Graph-Based Time Series Models addresses a central problem in timeseries forecasting and graph-structure-learning…
Graph-to-Text Generation Introduction & Motivation Graph-to-Text Generation addresses a central problem in generative generation and graph-coverage-accuracy synthesis: how…
graph traversal bfs, graph traversal, traversal bfs
Graph Traversal BFS Introduction & Motivation Graph Traversal BFS addresses a central problem in algorithms process control and traversal-latency-linear prediction: how to Predict…
graph traversal dfs, graph traversal, traversal dfs
Graph Traversal DFS Introduction & Motivation Graph Traversal DFS addresses a central problem in algorithms process control and traversal-time-linear prediction: how to Predict…
graph neural networks
Graph U-Net is an encoder-decoder graph architecture with learned pooling and unpooling across hierarchical resolutions - It captures global context through coarsening while…
gnn upsampling, graph generation
Graph unpooling is a graph neural network operation that reconstructs higher-resolution graphs from pooled representations — the inverse of pooling, used in graph autoencoders…
graph neural networks
GraphVAE is a Variational Autoencoder designed for graph-structured data that generates entire molecular graphs in a single forward pass — simultaneously producing the adjacency…
Graph Random Walk Generation Introduction & Motivation Graph Random Walk Generation addresses a central problem in graph network representation and walk-diversity learning: how…
graph neural networks
Graph Wavelets are localized, multi-scale basis functions defined on graphs that enable simultaneous localization in both the vertex (spatial) domain and the spectral (frequency)…
graph neural networks
GraphAF is autoregressive flow-based molecular graph generation with exact likelihood optimization. - It sequentially constructs molecules while maintaining tractable probability…
GraphCL Contrastive Self-Supervised Learning on Graphs Introduction & Motivation GraphCL Contrastive Self-Supervised Learning on Graphs addresses a central problem…
graphene barrier layer defect prediction machine learning, graphene barrier, layer defect prediction, cvd, graphene barrier layer defect prediction, graphene barrier layer
Graphene Barrier Layer Defect Prediction with Machine Learning Introduction & Motivation Graphene Barrier Layer Defect Prediction with Machine Learning addresses a central problem…
research
Graphene is an allotrope of carbon consisting of a single two-dimensional (2D) monolayer of sp²-hybridized carbon atoms tightly packed in a honeycomb hexagonal crystal lattice.…
graphene interconnect defect prediction, graphene interconnect defect, interconnect defect prediction, graphene interconnect, interconnect defect, defect prediction
Graphene Interconnect Defect Prediction with Machine Learning Introduction & Motivation Graphene Interconnect Defect Prediction with Machine Learning addresses a central problem…
graphene synthesis quality prediction, graphene synthesis quality, synthesis quality prediction, graphene synthesis, synthesis quality, quality prediction
Graphene Synthesis Quality Prediction with Machine Learning Introduction & Motivation Graphene Synthesis Quality Prediction with Machine Learning addresses a central problem…
thermal management
Graphene TIM is a thermal interface material incorporating graphene to enhance in-plane and through-plane heat transport - It targets lower interface resistance with mechanically…
graphene bandgap engineering, graphene contact resistance, graphene high frequency, graphene rf applications
Graphene Transistor Fabrication: Dirac Physics, Bandgap Engineering & High-Frequency RF Devices When isolated as a free-standing monolayer, graphene—a two-dimensional honeycomb…
graph neural networks
GraphGen is an autoregressive graph generation model that represents graphs as sequences of canonical orderings and uses deep recurrent networks to learn the distribution over…
GUI, WIMP, Xerox Alto, Xerox PARC, Apple Lisa, Macintosh 1984, desktop metaphor
A graphical user interface, or GUI, is a way of operating a computer by looking at and manipulating pictures on a screen — windows, icons, menus, buttons and a pointer — instead…
gddr, gddr6, gddr6x, gddr7, graphics ddr, graphics dram, lpddr, lpddr5x, mobile dram, mobile memory, low power dram, gddr vs lpddr
GDDR and LPDDR are the two mass-market high-performance flavors of DRAM, and they exist because bandwidth and power pull in opposite directions. Every modern system needs working…
gpu, CUDA, GeForce 256, tensor core, SIMT, AlexNet, VRAM
A graphics processing unit is a processor built around thousands of small arithmetic units that execute the same operation on huge batches of data at once, originally designed…
graphics processor memory bandwidth yield prediction, graphics processor memory, processor memory bandwidth, memory bandwidth yield, bandwidth yield prediction, graphics processor
Graphics Processor Memory Bandwidth Yield Prediction with Machine Learning Introduction & Motivation Graphics Processor Memory Bandwidth Yield Prediction with Machine Learning…
graph neural networks
GraphNVP is a normalizing-flow framework for invertible graph generation and likelihood evaluation - Invertible transformations map between latent variables and graph structures…
query, flexible
GraphQL is the query language for APIs and runtime for executing queries developed by Meta that allows clients to request exactly the data they need — eliminating…
graphql query language, graphql query, query language
GraphQL Query Language Introduction & Motivation GraphQL Query Language addresses a central problem in programming process control and over-fetching-under-fetching-elimination…
graph neural networks
GraphRNN is an autoregressive deep generative model that constructs graphs sequentially — adding one node at a time and deciding which edges connect each new node to previously…
graph neural networks
GraphRNN is a generative model that sequentially constructs graphs using recurrent neural-network decoders - Node and edge generation are autoregressively modeled to learn graph…
graph neural networks
GraphSAGE (Graph Sample and AGgrEgate) is an inductive graph neural network framework that learns node embeddings by sampling and aggregating features from local neighborhoods…
graph neural networks
GraphSAGE is an inductive graph-learning method that samples and aggregates neighborhood features to produce node embeddings - Parameterized aggregators combine sampled neighbor…
graph neural networks
GraphTransformer is transformer-based graph modeling that injects structural encodings into self-attention. - It extends global attention to graphs while preserving topology…
graph neural networks
GraphVAE is a variational autoencoder architecture for probabilistic graph generation - It learns latent distributions that decode into graph structures and attributes. What Is…
grasping manipulation grasp, grasping manipulation, manipulation grasp
Grasping Manipulation Grasp Introduction & Motivation Grasping Manipulation Grasp addresses a central problem in robotics process control and grasp-planning-grasp-point…
edge coupler, silicon photonics, fiber coupling, diffraction, wavelength sensitivity, packaging
Grating Coupler vs. Edge Coupler: Fiber-to-Chip Interface Light traveling inside a silicon photonics waveguide eventually has to transfer into or out of an optical fiber, and…
gravitational search algorithm, gravitational search, search algorithm
Gravitational Search Algorithm Introduction & Motivation Gravitational Search Algorithm addresses a central problem in ml process control and solution-quality-optimization…
design & verification
Gray Code is a binary encoding where adjacent values differ by one bit, minimizing transition ambiguity - It improves robustness in asynchronous pointer transfer and position…
gisaxs, grazing-incidence small-angle x-ray scattering, grazing incidence small angle x-ray scattering, gisaxs thin film, gisaxs metrology
Grazing-incidence small-angle X-ray scattering turns weak nanoscale density variations at a surface or within a thin film into a two-dimensional reciprocal-space pattern.…
grazing incidence x-ray diffraction, gixrd, gixd, grazing incidence diffraction, thin film gixrd
Grazing-incidence X-ray diffraction makes a weak crystalline film visible by sending the incident beam almost parallel to its surface. The long path through the film raises…
Great Expectations Declarative Data Quality Suites Introduction & Motivation Great Expectations Declarative Data Quality Suites addresses a central problem in (subject) assurance…
beam search, decoding, sampling, top-k, top-p, nucleus, temperature, generation
Greedy decoding is an autoregressive token generation strategy that deterministically selects the single token with the maximum conditional probability at every discrete decode…
greedy algorithm correctness, greedy algorithm, algorithm correctness
Greedy Algorithm Correctness Introduction & Motivation Greedy Algorithm Correctness addresses a central problem in algorithms process control and greedy-choice-property…
greedy search, greedy, argmax decoding, greedy decoding vs beam search, greedy generation
Greedy decoding selects only the single highest-probability next token at every individual generation step, committing immediately and irrevocably to that one specific token…
inference
Greedy decoding's defining characteristic, always selecting the single highest-probability token with no randomness, makes it fully deterministic and computationally cheap, but…
text generation
Greedy decoding's fundamental lack of any sequence-revision capability is precisely the specific limitation that beam search, by tracking several candidate partial sequences…
Greedy Equivalence Search GES for Observational DAGs Introduction & Motivation Greedy Equivalence Search GES for Observational DAGs addresses a central problem in causal inference…
Greedy Interventional Equivalence Search GIES Introduction & Motivation Greedy Interventional Equivalence Search GIES addresses a central problem in causal inference and (target)…
metrology
Greek cross is a sheet resistance measurement pattern — a symmetric four-point probe structure shaped like a plus sign (+), providing more accurate sheet resistance measurements…
environmental & sustainability
Green chemistry is the design of chemical products and processes that minimize hazardous substances and waste - Principles emphasize safer reagents, efficient reactions…
facility
Green fab refers to environmentally friendly fab design and operations that minimize resource consumption and environmental impact while maintaining manufacturing excellence.…