n-beats, n-beats, time series models
N-BEATS is a neural basis expansion analysis architecture for interpretable time series forecasting using forward and backward forecast stacks.
265 technical terms and definitions
N-BEATS is a neural basis expansion analysis architecture for interpretable time series forecasting using forward and backward forecast stacks.
Measure text similarity using shared n-grams.
Donors (P As Sb) add electrons.
N classes with K examples each.
nFETs in substrate pFETs in n-well.
n8n is open source workflow automation. Self-hostable.
Q-learning for continuous actions.
Naive Bayes is simple probabilistic classifier. Fast, baseline.
Replace names to test bias.
Generate names for products, companies, projects.
Identify entities in text.
NaN/Inf in training means numerical issues. Check for division by zero, log of negative, overflow. Lower LR or fix code.
nanoGPT is minimal GPT implementation by Karpathy. Educational. Train on Shakespeare.
Mechanically press pattern into resist.
GAA variant with horizontal sheet-like channels.
Stack multiple nanosheets vertically.
Nanoscale surface topography.
GAA variant with cylindrical nanowire channels.
Neural Attentive Recommendation Machine combines RNNs with attention mechanisms to capture both sequential patterns and main purposes in sessions.
Comprehend story structure.
Long narrative understanding.
QA on stories and books.
Cell-based neural architecture search discovers repeatable computational blocks that are stacked for full networks.
NAS-Bench provides standardized benchmarks with pre-computed architecture performance metrics to enable reproducible and efficient NAS research.
Reinforcement learning agents for NAS explore architecture spaces using policy gradients to maximize validation performance.
Neural Architecture Search automates model design. Finds optimal architectures for given constraints.
Nash equilibrium in multi-agent RL represents a stable state where no agent can improve their policy unilaterally given the policies of other agents.
Neural Architecture Search Without Training uses gradient magnitude statistics at initialization to predict architecture performance.
Strip naturally formed oxide before processing.
Natural convection cooling relies on buoyancy-driven airflow without fans suitable for low-power applications with less noise.
Human-written instruction data.
Determine entailment/contradiction.
QA dataset from real search queries.
Natural Questions contains real user queries to search engines with answers.
Navigate environments using language instructions.
Model NBTI degradation.
Monitor threshold voltage shift from NBTI.
Optimized collective operations.
Neural Collaborative Filtering framework unifies GMF and MLP pathways through concatenation for expressive recommendation models.
NCHW layout stores tensors in batch-channel-height-width order preferred by some accelerators.
Different tensor layout formats.
Ranking quality metric.
Normalized Discounted Cumulative Gain optimization directly targets ranking quality metrics.
Normalized Discounted Cumulative Gain measures ranking quality with position weighting.
Find similar examples.
Find similar examples for deduplication.
Operate near threshold voltage for ultra-low power.
Threshold voltage shift in pFETs under negative bias and temperature.
More realistic model with defect clustering.
Negative binomial yield model extends Poisson by allowing defect clustering through additional variance parameter.