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Showing result 1 - 5 of 19 essays matching the above criteria.

1. 1. Towards topology-aware Variational Auto-Encoders : from InvMap-VAE to Witness Simplicial VAE

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

   Author : Aniss Aiman Medbouhi; [2022]
   Keywords : Variational Auto-Encoder; Nonlinear dimensionality reduction; Generative model; Inverse projection; Computational topology; Algorithmic topology; Topological Data Analysis; Data visualisation; Unsupervised representation learning; Topological machine learning; Betti number; Simplicial complex; Witness complex; Simplicial map; Simplicial regularization.; Variations autokodare; Ickelinjär dimensionalitetsreducering; Generativ modell; Invers projektion; Beräkningstopologi; Algoritmisk topologi; Topologisk Data Analys; Datavisualisering; Oövervakat representationsinlärning; Topologisk maskininlärning; Betti-nummer; Simplicielt komplex; Vittneskomplex; Simpliciel avbildning; Simpliciel regularisering.;

   Abstract : Variational Auto-Encoders (VAEs) are one of the most famous deep generative models. After showing that standard VAEs may not preserve the topology, that is the shape of the data, between the input and the latent space, we tried to modify them so that the topology is preserved. READ MORE

3. 2. Cooperative security log analysis using machine learning : Analyzing different approaches to log featurization and classification

   University essay from Linköpings universitet/Databas och informationsteknik

   Author : Fredrik Malmfors; [2022]
   Keywords : Machine learning; word embeddings; deep learning; LSTM; CNN; auto encoder; NLP; natural language processing; intrusion detection; log analysis; logs; log classification; anomaly detection; supervised learning; unsupervised learning;

   Abstract : This thesis evaluates the performance of different machine learning approaches to log classification based on a dataset derived from simulating intrusive behavior towards an enterprise web application. The first experiment consists of performing attacks towards the web app in correlation with the logs to create a labeled dataset. READ MORE

4. 3. Outlier detection with ensembled LSTM auto-encoders on PCA transformed financial data

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

   Author : Love Stark; [2021]
   Keywords : Long Short-Term Memory Recurrent Neural Networks LSTM ; Ensemble learning; Auto-Encoder; anomaly detection; financial data; deep learning; Principal Component Analysis PCA ; Long Short-Term Memory Recurrent Neural Networks LSTM ; Ensemble lärande; Auto-Encoder; avvikelse detektering; finansiell data; djupinlärning; Principal Component Analysis PCA ;

   Abstract : Financial institutions today generate a large amount of data, data that can contain interesting information to investigate to further the economic growth of said institution. There exists an interest in analyzing these points of information, especially if they are anomalous from the normal day-to-day work. READ MORE

5. 4. A Machine Learning Approach for Comprehending Cosmic Expansion

   University essay from KTH/Fysik

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

   Abstract : 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. READ MORE

6. 5. Anomaly Detection on Gas Turbine Time-series’ Data Using Deep LSTM-Autoencoder

   University essay from Umeå universitet/Institutionen för datavetenskap

   Author : Marzieh Farahani; [2021]
   Keywords : ;

   Abstract : Anomaly detection with the aim of identifying outliers plays a very important role in various applications (e.g., online spam, manufacturing, finance etc.). READ MORE