dendrogram, manufacturing operations
Dendrograms visualize hierarchical clustering results as tree diagrams.
656 technical terms and definitions
Dendrograms visualize hierarchical clustering results as tree diagrams.
As transistors shrink voltage and power scale down proportionally (ended around 2005).
Core framework for diffusion-based generation.
Reconstruct from corrupted input.
Denoising score matching trains energy models by learning to denoise samples corrupted with known noise distributions.
Learn scores through denoising.
Control generation vs input preservation.
Generate captions for regions.
Generate captions for image regions.
Create detailed 3D maps.
Standard model where all parameters activate for every input.
Adapt ViT for segmentation/detection.
Use dense embeddings for retrieval.
Dense retrieval uses neural embeddings to find semantically similar documents.
Dense retrieval uses embeddings for similarity. Bi-encoders efficient. FAISS for vector search.
Use neural embeddings to retrieve relevant documents vs sparse keyword methods.
Learn attention patterns.
Combine neural embeddings with keyword search.
Convert dense to MoE model.
DenseNAS enables efficient one-shot search in dense spaces through dimension-extended sampling.
Add Gaussians where needed.
Quantum mechanical method for electronic structure.
Quantum correction technique.
Available states per energy.
Region near surface free of precipitates.
Handle library dependencies.
Analyze grammatical dependencies.
Width of depleted region.
Film thickness grown per unit time.
Model film growth.
Depreciation allocates capital equipment costs over useful life in accounting.
Reverse-engineer device by layer removal.
Densify sparse depth.
Fill in sparse depth maps.
Depth conditioning guides generation using depth maps preserving spatial structure.
Monocular depth prediction.
Estimate depth from motion.
Merge depth from multiple sources.
Condition on depth information.
Range of wafer height where image stays in focus.
Acceptable focus range.
Estimate uncertainty in depth.
Improve initial depth estimates.
Depthwise convolutions apply separate filters per input channel without cross-channel interaction.
Factorize convolution into depthwise and pointwise.
Depthwise separable convolutions factorize standard convolutions into depthwise and pointwise operations reducing computation.
Depthwise temporal convolutions process each channel independently across time.
Operate below maximum ratings for reliability.
Derivative products modify platform designs for specific applications reducing NRE.
Descript audio codec uses neural compression with VQ enabling high-quality speech synthesis from tokens.