Rapid stereo-vision enhanced face detection. - Sergey Kosov; Kristina Scherbaum; Kamil Faber; Thorsten Thormählen; Hans-Peter Seidel (ICIP, 2009)

WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Michael Baron; Nathalie Japkowicz (IEEE BigData, 2021)

Autoencoder-based IDS for cloud and mobile devices. - Kamil Faber; Lukasz Faber; Bartlomiej Sniezynski (CCGRID, 2021)

Ensemble neuroevolution based approach for multivariate time series anomaly detection. - Kamil Faber; Dominik Zurek; Marcin Pietron; Kamil Pietak (CoRR, 2021)

Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection. - Marcin Pietron; Dominik Zurek; Kamil Faber (CoRR, 2021)

Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection. - Kamil Faber; Marcin Pietron; Dominik Zurek (Entropy, 2021)

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. - Indranil Sur; Zachary Daniels; Abrar Rahman; Kamil Faber; Gianmarco J. Gallardo; Tyler L. Hayes; Cameron E. Taylor; Mustafa Burak Gurbuz; James Seale Smith; Sahana Pramod Joshi; Nathalie Japkowicz; Michael Baron; et al. (AIMLSystems, 2022)

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. - Zachary Alan Daniels; Aswin Raghavan; Jesse Hostetler; Abrar Rahman; Indranil Sur; Michael R. Piacentino; Ajay Divakaran; Roberto Corizzo; Kamil Faber; Nathalie Japkowicz; Michael Baron; James Seale Smith; et al. (CoLLAs, 2022)

Active Lifelong Anomaly Detection with Experience Replay. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (DSAA, 2022)

LIFEWATCH: Lifelong Wasserstein Change Point Detection. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Michael Baron; Nathalie Japkowicz (IJCNN, 2022)

Distributed Continual Intrusion Detection: A Collaborative Replay Framework. - Kamil Faber; Bartlomiej Sniezynski; Roberto Corizzo (IEEE Big Data, 2023)

Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ECAI, 2023)

Transformed-*: A domain-incremental lifelong learning scenario generation framework. - Dominik Zurek; Roberto Corizzo; Michal Karwatowski; Marcin Pietron; Kamil Faber (IJCNN, 2023)

Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (CoRR, 2023)

AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

VLAD: Task-agnostic VAE-based lifelong anomaly detection. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (Neural Networks, 2023)

RLEM: Deep Reinforcement Learning Ensemble Method for Aircraft Recovery Problem. - Dominik Zurek; Marcin Pietron; Szymon Piórkowski; Michal Karwatowski; Kamil Faber (IEEE Big Data, 2024)

A Deep Double Q-Learning as a SDLS support in solving LABS problem. - Dominik Zurek; Marcin Pietron; Kamil Pietak; Kamil Faber (ESANN, 2024)

AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo; Anna Wójcik (GECCO Companion, 2024)

Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ICCS (3), 2024)

Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (IEEE Access, 2024)

AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2024)

Solving Multi-Goal Robotic Tasks with Decision Transformer. - Paul Gajewski; Dominik Zurek; Marcin Pietron; Kamil Faber (CoRR, 2024)

From MNIST to ImageNet and back: benchmarking continual curriculum learning. - Kamil Faber; Dominik Zurek; Marcin Pietron; Nathalie Japkowicz; Antonio Vergari; Roberto Corizzo (Mach. Learn., 2024)

TinySubNets: An Efficient and Low Capacity Continual Learning Strategy. - Marcin Pietron; Kamil Faber; Dominik Zurek; Roberto Corizzo (AAAI, 2025)

pyCLAD: The universal framework for continual lifelong anomaly detection. - Kamil Faber; Bartlomiej Sniezynski; Nathalie Japkowicz; Roberto Corizzo (SoftwareX, 2025)

AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (IEEE Trans. Neural Networks Learn. Syst., 2025)

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection. - Kamil Faber; Marcin Pietron; Dominik Zurek; Roberto Corizzo (CoRR, 2025)