ternary networks, model optimization
Ternary networks use three-level weights providing expressiveness between binary and full precision.
9,967 technical terms and definitions
Ternary networks use three-level weights providing expressiveness between binary and full precision.
Use three values (−1 0 +1).
Generate tests from specifications.
Test costs encompass wafer probe package test and burn-in expenses.
Expense of testing per unit.
Test coverage quantifies the percentage of device functionality or potential defects detected by a test program or suite.
Percentage of defects detected by test.
Test die contain monitoring structures for process characterization without functional circuits.
Test escape rate measures fraction of defective devices passing test and reaching customers.
Test escapes are defective devices that pass testing and reach customers requiring analysis to improve test program effectiveness.
AI generates unit tests. Increase coverage. Understand code intent.
Automatically create unit tests for code.
LLMs generate unit tests from code or specs. Helps increase coverage and catch edge cases.
Test point insertion adds observability or controllability improving fault detection.
Test programs define the sequence of measurements biasing conditions and pass-fail criteria for automated semiconductor device characterization.
Duration of electrical testing.
Input patterns to verify chip functionality.
Adapt model during inference without labels.
Average predictions over augmentations.
Augment during inference and average.
Update model at test time.
I help you design unit/integration tests, choose frameworks, and think about edge cases and regression protection.
Tetrad implements causal discovery algorithms like PC and FCI for learning directed acyclic graphs from data.
Encode prompts (CLIP ViT-L).
text-generation-webui provides full-featured LLM interface. Many features. Community project.
Hugging Face's optimized serving solution for LLMs.
Predict masked spans of varying length.
Randomly shuffle tokens.
Edit images using text prompts.
Generate 3D from text.
Text-to-3D methods generate three-dimensional models from textual descriptions.
Ensure generated images match text.
Create images from text descriptions (DALL-E Midjourney Stable Diffusion).
Generate images from text.
Convert written text into spoken audio with natural prosody.
Convert questions to SQL queries.
Generate videos from text.
Text-to-video models generate video sequences from textual descriptions.
Generate video clips from text descriptions.
Learn new tokens from images.
Textual inversion learns new tokens representing concepts for personalized generation.
Learn new tokens representing specific concepts for generation.
Study preferred crystal orientations.
Vision models relying on texture over shape.
Create surface textures.
Texture synthesis generates surface appearance through learned or procedural methods.
Generate realistic textures.
Classic information retrieval metric.
Temporal Graph Attention Network uses temporal encoding and functional time encoding for dynamic graph learning.
Temporal Graph Convolutional Network combines graph convolutions with gated recurrent units to capture spatial and temporal dependencies in dynamic graphs.