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;...

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...

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

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

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

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

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

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...

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...

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

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...

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...

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...

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

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

significantly. CCMs have also been applied to latent learning frameworks, where the learning problem is defined over a latent representation layer. Since the notion...

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

DALLE-2 for text to image generation. Dynamic representation learning methods generate latent embeddings for dynamic systems such as dynamic networks. Since...

learning." arXiv preprint arXiv:1708.05866 (2017). https://arxiv.org/abs/1708.05866 Hafner, D. et al. "Dream to control: Learning behaviors by latent...

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

Jordan, Michael I; Lafferty, John (January 2003). "Latent Dirichlet allocation". Journal of Machine Learning Research. 3: pp. 993–1022. Archived from the original...

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