AI Factory Glossary

gradient compression techniques, distributed training

Reduce gradient communication.

gradient compression,communication

Gradient compression reduces communication in distributed training. Quantize or sparsify gradients.

gradient episodic memory, gem, continual learning

Constrain gradients to preserve knowledge.

gradient flow in deep vits, computer vision

Maintaining gradients in very deep models.

gradient flow preservation,model training

Maintain gradient flow in sparse networks.

gradient masking, ai safety

Make gradients uninformative.

gradient noise, optimization

Add noise to gradients for regularization.

gradient normalization, optimization

Normalize gradient magnitude.

gradient penalty, generative models

Regularize gradient magnitude (GANs).

gradient quantization for communication, distributed training

Quantize gradients for transmission.

gradient reversal layer, domain adaptation

Reverse gradients for adversarial training.

gradient scaling, optimization

Scale gradients to prevent underflow.

gradient sparsification, optimization

Send only significant gradient components.

gradient synchronization, distributed training

Aggregate gradients across devices.

gradient-based masking, nlp

Mask tokens with large gradients.

gradient-based nas, neural architecture

Optimize architecture with gradients.

gradient-based prompt tuning,fine-tuning

Optimize continuous prompt embeddings using gradients.

gradient-based pruning, model optimization

Gradient-based pruning estimates weight importance using gradient information.

gradient-based pruning,model optimization

Use gradients to determine importance.

gradient,backprop,backward pass

Backpropagation computes gradients via chain rule, flowing error from output to input. Gradients update weights via optimizer.

gradio,interface,demo

Gradio creates ML demo interfaces quickly. Hugging Face integration. Share instantly.

gradual rollout,deployment

Slowly increase traffic to new version.

gradual rollout,percentage,traffic

Gradually increase traffic to new model: 1%, 10%, 50%, 100%. Monitor metrics at each stage.

gradual unfreezing, fine-tuning

Unfreeze from top to bottom gradually.

grafana,dashboard,visualize

Grafana dashboards visualize metrics. Alerts on thresholds. Operations visibility.

grafana,mlops

Visualization platform for metrics.

grain boundaries, defects

Interfaces between crystallites.

grain boundary characterization, metrology

Analyze grain boundary structure and energy.

grain boundary energy, defects

Energy per area of boundary.

grain boundary segregation, defects

Impurities collect at boundaries.

grain growth in copper,beol

Increase grain size to reduce resistance.

grammar-based decoding, llm optimization

Grammar-based decoding generates text following formal grammar specifications.

grammar-based generation, graph neural networks

Grammar-based generation uses formal grammars to ensure syntactic validity of generated graphs.

grammar-based generation, text generation

Generate following formal grammar.

grammar-based sampling,structured generation

Sample tokens that conform to formal grammar.

grammar,spelling,check

Grammar and spelling correction. Style suggestions.

gran, gran, graph neural networks

Graph Recurrent Attention Networks generate graphs through sequential block-wise generation with recurrent state tracking for scalability.

granger causality, time series models

Granger causality tests whether past values of one time series provide statistically significant information for predicting another series.

granger non-causality, time series models

Granger non-causality tests null hypothesis that past values of one series don't help predict another.

granite surface plate,metrology

Flat reference for mechanical measurements.

graph alignment, graph algorithms

Find correspondence between graphs.

graph attention networks (gat),graph attention networks,gat,graph neural networks

Use attention in GNNs.

graph canonization, graph algorithms

Create unique representation of graph.

graph clustering, graph algorithms

Group similar nodes.

graph coarsening, graph algorithms

Create simplified version of graph.

graph completion, graph neural networks

Graph completion predicts missing nodes or edges in incomplete graphs for knowledge graph construction.

graph convnet marl, reinforcement learning advanced

Graph convolutional networks in MARL aggregate information over agent interaction graphs capturing structured multi-agent dependencies.

graph convolution, graph neural networks

Graph convolution generalizes convolutional operations to irregular graph structures by aggregating features from neighboring nodes with learnable weights.

graph convolutional networks (gcn),graph convolutional networks,gcn,graph neural networks

Convolutional operations on graphs.

graph edit distance, graph algorithms

Measure dissimilarity via edit operations.