Results for "trial-and-error"

A single attention mechanism within multi-head attention.

Set of all actions available to the agent.

Strategy mapping states to actions.

Separates planning from execution in agent architectures.

Optimizing policies directly via gradient ascent on expected reward.

Neural networks that operate on graph-structured data by propagating information along edges.

Extension of convolution to graph domains using adjacency structure.

Models that learn to generate samples resembling training data.

Autoencoder using probabilistic latent variables and KL regularization.

Exact likelihood generative models using invertible transforms.

Pixel-level separation of individual object instances.

Combining signals from multiple modalities.

Attention between different modalities.

Generating human-like speech from text.

Detects trigger phrases in audio streams.

Monte Carlo method for state estimation.

Models effects of interventions (do(X=x)).

What would have happened under different conditions.

Model execution path in production.

Incrementally deploying new models to reduce risk.

Running predictions on large datasets periodically.

Maintaining two environments for instant rollback.

Agent calls external tools dynamically.

Number of steps considered in planning.

Scaling law optimizing compute vs data.

Vectors with zero inner product; implies independence.

Variable whose values depend on chance.

Measure of spread around the mean.

Measures joint variability between variables.

Sample mean converges to expected value.