Results for "distribution distance"

Measure of vector magnitude; used in regularization and optimization.

Sampling from easier distribution with reweighting.

Updated belief after observing data.

Train/test environment mismatch.

Sum of independent variables converges to normal distribution.

Attention where queries/keys/values come from the same sequence, enabling token-to-token interactions.

Retrieval based on embedding similarity rather than keyword overlap, capturing paraphrases and related concepts.

Inputs crafted to cause model errors or unsafe behavior, often imperceptible in vision or subtle in text.

Encodes positional information via rotation in embedding space.

Computing collision-free trajectories.

Finding routes from start to goal.

Identifying suspicious transactions.

Deep learning system for protein structure prediction.

Groups adopting extreme positions.

Bayesian parameter estimation using the mode of the posterior distribution.

Measures divergence between true and predicted probability distributions.

Measures how one probability distribution diverges from another.

Models that learn to generate samples resembling training data.

Autoencoder using probabilistic latent variables and KL regularization.

Belief before observing data.

Differences between training and deployed patient populations.

How well a model performs on new data drawn from the same (or similar) distribution as training.

Graphical model expressing factorization of a probability distribution.

Diffusion model trained to remove noise step by step.

Learns the score (∇ log p(x)) for generative sampling.

Generator produces limited variety of outputs.

Shift in model outputs.

Describes likelihoods of random variable outcomes.

Eliminating variables by integrating over them.

Differences between training and inference conditions.