Sökning: "Probabilistisk Maskininlärning"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden Probabilistisk Maskininlärning.

1. 1. Reinforcement Learning for Market Making

   Master-uppsats, KTH/Matematisk statistik

   Författare :Simon Carlsson; August Regnell; [2022]
   Nyckelord :Reinforcement learning; Market making; Deep reinforcement learning; Limit order book; Algorithmic trading; High-frequency trading; Machine learning; Artificial intelligence; Q-learning; DDQN; Förstärkningsinlärning; Market making; Djup förstärkningsinlärning; Limitorderbok; Algoritmisk handel; Högfrekvenshandel; Maskininlärning; Artificiell intelligens; Q-learning; DDQN;

   Sammanfattning : Market making – the process of simultaneously and continuously providing buy and sell prices in a financial asset – is rather complicated to optimize. Applying reinforcement learning (RL) to infer optimal market making strategies is a relatively uncharted and novel research area. LÄS MER

3. 2. A Machine Learning Approach for Comprehending Cosmic Expansion

   Master-uppsats, KTH/Fysik

   Författare :Ludvig Doeser; [2021]
   Nyckelord :Cosmology; Cosmic expansion; Galaxy Images; Machine learning; Kosmologi; kosmisk expansion; galaxbilder; maskininlärning;

   Sammanfattning : This thesis aims at using novel machine learning techniques to test the dynamics of the Universe via the cosmological redshift-distance test. Currently, one of the most outstanding questions in cosmology is the physical cause of the accelerating cosmic expansion observed with supernovae. LÄS MER

4. 3. Modelling approach and avoidance behaviour : A deep learning approach to understand the human olfactory system

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Frans Nordén; [2021]
   Nyckelord :Probabilistic Machine Learning; Variational Recurrent Neural Network; EEG; Approach and Avoidance behaviour; Frontal alpha asymmetry; Probabilistisk Maskininlärning; Variational Recurrent Neural Network; EEG; Approach and Avoidance behaviour; Frontal alpha asymmetri;

   Sammanfattning : In this thesis we examine the question whether it is possible to model approach and avoidance behaviour with probabilistic machine learning. The results from this project will primarily aid in our collective understanding of human existence. LÄS MER

5. 4. Prediction of Dose Probability Distributions Using Mixture Density Networks

   Master-uppsats, KTH/Matematisk statistik

   Författare :Viktor Nilsson; [2020]
   Nyckelord :Applied mathematics; machine learning; deep learning; mixture density network; dose planning; Tillämpad matematik; maskininlärning; djupinlärning; mixturdensitetsnätverk; dosplannerning;

   Sammanfattning : In recent years, machine learning has become utilized in external radiation therapy treatment planning. This involves automatic generation of treatment plans based on CT-scans and other spatial information such as the location of tumors and organs. LÄS MER

7. 5. Image Distance Learning for Probabilistic Dose–Volume Histogram and Spatial Dose Prediction in Radiation Therapy Treatment Planning

   Master-uppsats, KTH/Matematisk statistik

   Författare :Ivar Eriksson; [2020]
   Nyckelord :Radiation therapy; automated planning; machine learning; autoencoder; distance optimisation; sparse pseudo-input Gaussian process; kernel density estimation; dose mimicking; dose–volume histogram; Strålbehandling; automatiserad dosplanering; maskininlärning; autoencoder; distansoptimering; glesa Gaussiska processer; sannolikhets-fördelnings-estimering; dosrekonstruktion; dos–volymhistogram;

   Sammanfattning : Construction of radiotherapy treatments for cancer is a laborious and time consuming task. At the same time, when presented with a treatment plan, an oncologist can quickly judge whether or not it is suitable. This means that the problem of constructing these treatment plans is well suited for automation. LÄS MER