Christofer Fellicious

Orcid: 0000-0001-7487-7110

According to our database1, Christofer Fellicious authored at least 17 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
CoRECT: A Framework for Evaluating Embedding Compression Techniques at Scale.
Proceedings of the Advances in Information Retrieval, 2026

2025
Bridging the Semantic Gap in Virtual Machine Introspection and Forensic Memory Analysis.
CoRR, March, 2025

Malware Detection based on API calls.
CoRR, February, 2025

Bridging the gap: Applying machine learning techniques in digital forensics.
PhD thesis, 2025

MemBERT: Foundation model for memory forensics.
Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing, 2025

On the Suitability of Pre-trained Foundational LLMs for Analysis in German Legal Education.
Proceedings of the Machine Learning, Optimization, and Data Science, 2025

2024
API traces for malware detection.
Dataset, April, 2024

Datenbank-Spektrum, March, 2024

DriftGAN: Using historical data for Unsupervised Recurring Drift Detection.
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024

PointerKex: A Pointer-Based SSH Key Extraction Method.
Proceedings of the Machine Learning, Optimization, and Data Science, 2024

SUDS: A Strategy for Unsupervised Drift Sampling.
Proceedings of the 36th IEEE International Conference on Tools with Artificial Intelligence, 2024

2022
SmartKex: Machine Learning Assisted SSH Keys Extraction From The Heap Dump.
CoRR, 2022

"The Need for Speed": Extracting Session Keys From the Main Memory Using Brute-force and Machine Learning.
Proceedings of the IEEE International Conference on Trust, 2022

Pooling Graph Convolutional Networks for Structural Performance Prediction.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022

Neural Network Based Drift Detection.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022

2020
Effects of Random Seeds on the Accuracy of Convolutional Neural Networks.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

2018
Transfer Learning and Organic Computing for Autonomous Vehicles.
CoRR, 2018


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