Essays about: "Probabilistic Machine Learning"

Showing result 21 - 25 of 49 essays containing the words Probabilistic Machine Learning.

1. 21. Machine Learning for Ambulance Demand Prediction in Stockholm County : Towards efficient and equitableDynamic Deployment Systems

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Emil Kerakos; Oscar Lindgren; Vladislav Tolstoy; [2020]
   Keywords : ;

   Abstract : Pre-hospital care is a widely discussed subject with many actors working on figuring out what factors determine the outcome for the patient and how those factors can be affected. One factor believed to have a major impact on patient outcome is ambulance response time. A proposed way to improve response time is dynamic deployment systems. READ MORE

3. 22. An ensemble learning approach based on decision trees and probabilistic argumentation

   University essay from Umeå universitet/Institutionen för datavetenskap

   Author : Istiak Ahmed; [2020]
   Keywords : ;

   Abstract : This research discusses a decision support system that includes different machine learning approaches (e.g. ensemble learning, decision trees) and a symbolic reasoning approach (e.g. READ MORE

4. 23. Explainable Artificial Intelligence : How to Evaluate Explanations of Deep Neural Network Predictions using the Continuity Test

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Anna Hedström; [2020]
   Keywords : ;

   Abstract : With a surging appetite to leverage deep learning models as means to enhance decisionmaking, new requirements for interpretability are set. Renewed research interest has thus been found within the machine learning community to develop explainability methods that can estimate the influence of a given input feature to the prediction made by a model. READ MORE

5. 24. Probabilistic Regression using Conditional Generative Adversarial Networks

   University essay from Linköpings universitet/Statistik och maskininlärning

   Author : Joel Oskarsson; [2020]
   Keywords : machine learning; ml; regression; probabilistic; distribution; cgan; gan; conditional gan; adversarial networks; neural network; deep learning; f-gan; f-cgan; f-divergence; adversarial training; bimodal; heteroskedastic; mmd; maximum mean discrepancy; gmmn; generative moment matching network; conditional gmmn; ipm; kde; cgan evaluation; cgan regression; gan regression; cgan-regression; regression using gan; deep; nn; implicit; generative; conditional; model; complex noise; aleatoric; uncertainty; dctd; mdn; heteroskedastic regression; gp;

   Abstract : Regression is a central problem in statistics and machine learning with applications everywhere in science and technology. In probabilistic regression the relationship between a set of features and a real-valued target variable is modelled as a conditional probability distribution. READ MORE

6. 25. Understanding people movement and detecting anomalies using probabilistic generative models

   University essay from KTH/Matematisk statistik

   Author : Agnes Hansson; [2020]
   Keywords : Machine Learning; Unsupervised Learning; Generative Models; Auto-encoders; Gaussian Mixture Models; Maskininlärning; Oövervakad inlärning; generativa modeller; auto-encoders; gaussiska mixtur-modeller;

   Abstract : As intelligent access solutions begin to dominate the world, the statistical learning methods to answer for the behavior of these needs attention, as there is no clear answer to how an algorithm could learn and predict exactly how people move. This project aims at investigating if, with the help of unsupervised learning methods, it is possible to distinguish anomalies from normal events in an access system, and if the most probable choice of cylinder to be unlocked by a user can be calculated. READ MORE