There are 0 repository under latent topic.
Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity
Unofficial Implementation of E-LatentLPIPS(Ensembled-LatentLPIPS) of Diffusion2GAN
A High Quality (HD / 2K / 4K) Image Generation Using Stable Diffusion and Real-ESR / SwinIR /GFPGAN
Training RAVE, vschaos2, MSPrior and RAVE Latent Diffusion models on Kaggle or Colab
This repository contains as intuitive example on topic-modeling using regular LDA, and how GuidedLDA is better than regular LDA
Protests and agitations have long used as means for showing dissident towards social, political and economic issues in civil societies. In recent years we have witnessed a large number of protests across various geographies. Not to be left behind by similar trends in the rest of the world, South Africa, in recent years have witnessed a large number of protests. This paper uses the English text description of the protests to predict their time spans/durations. The descriptions consist of multiple causes of the protests, courses of actions etc. Next we used unsupervised (topic modeling) and supervised learning (decision trees) to predict the duration of protests. The results are very promising and close to 90% of accuracy in early predicting of the duration of protests.
A script that combines latent events and callbacks.
Code and data to reproduce "A Bayesian latent variable model for the optimal identification of disease incidence rates given information constraints"
custom node for ComfyUI
Rossman R., Yackulic C., Saunders S.P., Reid J., Davis R., and Zipkin E.F. 2016. Dynamic N-occupancy models: estimating demographic rates and local abundances from detection-nondetection data. Ecology. 97: 3300-3307.
Code used for the analysis in "Discernment of Mediator and Outcome Measurement in the PACE trial"
Latent factor GWAS; Multi-trait fine-mapping for any number of uncorrelated traits (and limited number of correlated traits)
Binary classification-models comparison
Using Latent Variable Analysis (LVA) to determine if there is an association between athletic activity and substance use while using level of depression as a mediator variable
This project presents a novel approach that integrates latent representations with recurrent architectures for depth modeling. It is designed for efficient learning and inference in complex environments.
Inference for Gaussian copula factor models and its application to causal discovery.
A collection of additional promise extending classes. Including a (from the outside) ResablePromise, CancelAblePromise and a latestLatent utility function.