1 – 15 of 281
- show: 15
- |
- sort: year (new to old)
Close
Embed this list
<iframe src=" "
width=" "
height=" "
allowtransparency="true"
frameborder="0">
</iframe>
- 2024
-
Mark
Predicting dust storm susceptibility: exploring control strategies with XGBoost models
(
- Master (Two yrs)
-
Mark
Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
(
- Master (Two yrs)
-
Mark
Forecasting during recession: Comparing the performance of machine learning and autoregressive models on the Swedish stock market
(
- Bach. Degree
-
Mark
Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data
2024) In Master Thesis in Geographical Information Science GISM01 20232(
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
-
Mark
Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
(
- Bach. Degree
-
Mark
Multivariate time series classification in time-sensitive environments using deep learning
(
- Master (Two yrs)
-
Mark
Prevalent Discord. Exploring and estimating the prevalence of the type of user disagreement on news media Facebook posts discussing the Colombian peace process (2020-2022)
(
- Master (Two yrs)
-
Mark
Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques
(
- Master (Two yrs)
- 2023
-
Mark
Modeling German Energy Market Hourly Profiles with a Focus on Variable Renewable Energy
(
- Master (One yr)
-
Mark
Modeling PFAS Transport in Groundwater - Exploring current approaches and evaluating parameter importance
(
- Prof. qual. >4 yrs
-
Mark
Predicting Protein Stability with Machine Learning
(
- Prof. qual. >4 yrs
-
Mark
Estimation of surface soil moisture from Sentinel-1 Synthetic Aperture Radar imagery using machine learning method
(
- Master (Two yrs)
-
Mark
Multi-Label Toxic Comment Classification Using Machine Learning: An In-Depth Study
(
- Master (Two yrs)
-
Mark
Energy Consumption Modelling for 5G Radio Base Stations with Machine Learning
(
- Master (Two yrs)
-
Mark
A spatio-temporal graph neural network framework for predicting usage efficiency of e-scooter sharing services
(
- Master (Two yrs)