Latent learning is the subconscious retention of information without reinforcement or motivation. In latent learning, one changes behavior only when there...

predictors. The interpretation of the latent spaces of machine learning models is an active field of study, but latent space interpretation is difficult to...

above). Latent learning is a technique used by Gutstein & Stump (2015) to mitigate catastrophic interference by taking advantage of transfer learning. This...

method of moments is shown to be effective in learning the parameters of latent variable models. Latent variable models are statistical models where in...

The Latent Diffusion Model (LDM) is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) group at LMU Munich. Introduced...

Latent inhibition (LI) is a technical term in classical conditioning, where a familiar stimulus takes longer to acquire meaning (as a signal or conditioned...

and to the alarm substance released by injured salmon. Latent learning is a form of learning that is not immediately expressed in an overt response;...

representation learning. Autoencoders consist of an encoder network that maps the input data to a lower-dimensional representation (latent space), and a...

measured. Such latent variable models are used in many disciplines, including engineering, medicine, ecology, physics, machine learning/artificial intelligence...

as purposive behaviorism. Tolman also promoted the concept known as latent learning first coined by Blodgett (1929). A Review of General Psychology survey...

of memory and learning Neural networks in the brain Sleep and learning Latent learning Memory consolidation Short-term memory versus working memory Long-term...

deep learning to extract meaningful features for a latent factor model for content-based music and journal recommendations. Multi-view deep learning has...

Chlordiazepoxide in laboratory mice studies impairs latent learning. Benzodiazepines impair learning and memory via their action on benzodiazepine receptors...

examining latent learning (which later inspired a new branch of anticipatory classifier systems (ACS)), and (12) the introduction of the first Q-learning-like...

Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured...

In natural language processing, latent Dirichlet allocation (LDA) is a Bayesian network (and, therefore, a generative statistical model) for modeling automatically...

within the latent space, rather than to a single point in that space. The decoder has the opposite function, which is to map from the latent space to the...

z=E_{\phi }(x)} , and refer to it as the code, the latent variable, latent representation, latent vector, etc. Conversely, for any z ∈ Z {\displaystyle...

Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between...

in a term space. A prominent example is probabilistic latent semantic analysis (PLSA). Latent Dirichlet allocation, which involves attributing document...

One-shot learning is an object categorization problem, found mostly in computer vision. Whereas most machine learning-based object categorization algorithms...

Large margin nearest neighbor Latent Dirichlet allocation Latent class model Latent semantic analysis Latent variable Latent variable model Lattice Miner...

variant of diffusion models, called latent diffusion model (LDM), developed in 2021 by the CompVis (Computer Vision & Learning) group at LMU Munich. Stable Diffusion...

Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

symptoms, in which case it is known as inactive or latent tuberculosis. A small proportion of latent infections progress to active disease that, if left...

error. Latent failures include contributory factors that may lie dormant for days, weeks, or months until they contribute to the accident. Latent failures...

revealing latent similarities across diverse applications. Feature extraction Dimensionality reduction Word embedding Neural network Reinforcement learning Bengio...

Machine learning. pp. 633–640. doi:10.1145/1273496.1273576. ISBN 9781595937933. S2CID 6045658. Hofmann, Thomas (1999). "Probabilistic Latent Semantic...

called live scan. A "latent print" is the chance recording of friction ridges deposited on the surface of an object or a wall. Latent prints are invisible...