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  2021 (9)
Device and method for anomaly detection on an input stream of events. Axenie, C.; Tudoran, R.; Bortoli, S.; Hassan, M. A. H.; and Brasche, G. April 29 2021. US Patent App. 17/140,882
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Efficient Operator Sharing Modulo Scheduling for Sum-Product Network Inference on FPGAs⋆. Sommer, L.; Axenie, C.; and Koch, A. . 2021.
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SPNC: Accelerating Sum-Product Network Inference on CPUs and GPUs. Sommer, L.; Halkenhäuser, M.; Axenie, C.; and Koch, A. In 2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP), pages 53–56, 2021. IEEE
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Less Is More: Learning Insights From a Single Motion Sensor for Accurate and Explainable Soccer Goalkeeper Kinematics. Lisca, G.; Prodaniuc, C.; Grauschopf, T.; and Axenie, C. IEEE Sensors Journal, 21(18): 20375–20387. 2021.
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OBELISC: Oscillator-Based Modelling and Control using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation. Axenie, C.; Shi, R.; Foroni, D.; Wieder, A.; Hassan, M. A. H.; Sottovia, P.; Grossi, M.; Bortoli, S.; and Brasche, G. In ECML-PKDD 2021, 2021.
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Data-Driven Discovery of Mathematical and Physical Relations in Oncology Data Using Human-Understandable Machine Learning. Kurz, D.; Sánchez, C. S.; and Axenie, C. Frontiers in Artificial Intelligence, 4: 158. 2021.
Data-Driven Discovery of Mathematical and Physical Relations in Oncology Data Using Human-Understandable Machine Learning [link]Paper   doi   link   bibtex   1 download  
The Multiple Dimensions of Networks in Cancer: A Perspective. Axenie, C.; Bauer, R.; and Martı́nez, Marı́a Rodrı́guez Symmetry, 13(9): 1559. 2021.
The Multiple Dimensions of Networks in Cancer: A Perspective [link]Paper   link   bibtex  
SPNC: Fast Sum-Product Network Inference. Sommer, L.; Axenie, C.; and Koch, A. . 2021.
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TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control. Axenie, C.; Shi, R.; Foroni, D.; Wieder, A.; Hassan, M. A. H.; Sottovia, P.; Grossi, M.; Bortoli, S.; and Brasche, G. In International Workshop on Advanced Analytics and Learning on Temporal Data, 2021.
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  2020 (11)
Learning Personalized Virtual Reality Avatars for Chemotherapy-Induced Peripheral Neuropathy Rehabilitation in Breast Cancer. Kurz, D.; and Axenie, C. In ONCOLOGY RESEARCH AND TREATMENT, volume 43, pages 166–166, 2020. KARGER ALLSCHWILERSTRASSE 10, CH-4009 BASEL, SWITZERLAND
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Tumor Characterization using Unsupervised Learning of Mathematical Relations within Breast Cancer Data. Axenie, C.; and Kurz, D. In International Conference on Artificial Neural Networks, pages 838–849, 2020. Springer, Cham
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A Framework for Learning Invariant Physical Relations in Multimodal Sensory Processing. Xiaorui, D.; Erdem, Y.; Schweizer, I.; and Axenie, C. arXiv preprint arXiv:2006.16607. 2020.
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Role of kinematics assessment and multimodal sensorimotor training for motion deficits in breast cancer chemotherapy-induced polyneuropathy: a perspective on virtual reality avatars. Axenie, C.; and Kurz, D. Frontiers in Oncology, 10: 1419. 2020.
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PRINCESS: Prediction of Individual Breast Cancer Evolution to Surgical Size. Axenie, C.; and Kurz, D. In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), pages 457–462, 2020. IEEE
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GANNSTER: Graph-Augmented Neural Network Spatio-Temporal Reasoner for Traffic Forecasting. Sánchez, C. S.; Wieder, A.; Sottovia, P.; Bortoli, S.; Baumbach, J.; and Axenie, C. In International Workshop on Advanced Analytics and Learning on Temporal Data, pages 63–76, 2020. Springer, Cham
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System and method for stream processing. Tudoran, R.; Bortoli, S.; Zhu, X.; Brasche, G.; and Axenie, C. September 10 2020. US Patent App. 16/827,122
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CHIMERA: Combining Mechanistic Models and Machine Learning for Personalized Chemotherapy and Surgery Sequencing in Breast Cancer. Axenie, C.; and Kurz, D. In International Symposium on Mathematical and Computational Oncology, pages 13–24, 2020. Springer, Cham
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Status and recommendations of technological and data-driven innovations in cancer care: focus group study. Kondylakis, H.; Axenie, C.; Bastola, D. K.; Katehakis, D. G; Kouroubali, A.; Kurz, D.; Larburu, N.; Macı́a, Iván; Maguire, R.; Maramis, C.; and others Journal of medical Internet research, 22(12): e22034. 2020.
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PERFECTO: Prediction of Extended Response and Growth Functions for Estimating Chemotherapy Outcomes in Breast Cancer. Kurz, D.; and Axenie, C. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 609–614, 2020. IEEE
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Glueck: Growth pattern learning for unsupervised extraction of cancer kinetics. Axenie, C.; and Kurz, D. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages 171–186, 2020. Springer, Cham
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  2019 (7)
Neural Network 3D Body Pose Tracking and Prediction for Motion-to-Photon Latency Compensation in Distributed Virtual Reality. Pohl, S.; Becher, A.; Grauschopf, T.; and Axenie, C. In International Conference on Artificial Neural Networks, pages 429–442, 2019. Springer, Cham
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NARPCA: Neural Accumulate-Retract PCA for Low-Latency High-Throughput Processing on Datastreams. Axenie, C.; Tudoran, R.; Bortoli, S.; Hassan, M. A. H.; and Brasche, G. In International Conference on Artificial Neural Networks, pages 253–266, 2019. Springer, Cham
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Meta-learning for avatar kinematics reconstruction in virtual reality rehabilitation. Axenie, C.; Becher, A.; Kurz, D.; and Grauschopf, T. In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), pages 617–624, 2019. IEEE
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Fuzzy Inference System for Risk Evaluation in Gestational Diabetes Mellitus. Sánchez, C. S.; Smyth, S.; Tully, E.; Griffin, J.; Heaphy, L.; Redmond, N.; Breathnach, F.; Baumbach, J.; and Axenie, C. In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), pages 947–952, 2019. IEEE
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Dimensionality Reduction for Low-Latency High-Throughput Fraud Detection on Datastreams. Axenie, C.; Tudoran, R.; Bortoli, S.; Hassan, M. A. H.; Sanchez, C. S.; and Brasche, G. In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), pages 1170–1177, 2019. IEEE
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An Online Incremental Clustering Framework for Real-Time Stream Analytics. Sanchez, C. S.; Tudoran, R.; Hassan, M. A. H.; Bortoli, S.; Brasche, G.; Baumbach, J.; and Axenie, C. In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), pages 1480–1485, 2019. IEEE
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SPICE: Streaming PCA Fault Identification and Classification Engine in Predictive Maintenance. Axenie, C.; Tudoran, R.; Bortoli, S.; Hassan, M. A. H.; Wieder, A.; and Brasche, G. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages 333–344, 2019. Springer, Cham
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  2018 (5)
Neuromorphic sensorimotor adaptation for robotic mobile manipulation: From sensing to behaviour. Mirus, F.; Axenie, C.; Stewart, T. C; and Conradt, J. Cognitive Systems Research, 50: 52–66. 2018.
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FPGA-based Hardware Accelerator for an Embedded Factor Graph with Configurable Optimization. Sugiarto, I.; Axenie, C.; and Conradt, J. Journal of Circuits, Systems, and Computers. 2018.
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Moira: A goal-oriented incremental machine learning approach to dynamic resource cost estimation in distributed stream processing systems. Foroni, D.; Axenie, C.; Bortoli, S.; Al Hajj Hassan, M.; Acker, R.; Tudoran, R.; Brasche, G.; and Velegrakis, Y. In Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics, pages 1–10, 2018.
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STARLORD: sliding window temporal accumulate-retract learning for online reasoning on datastreams. Axenie, C.; Tudoran, R.; Bortoli, S.; Hassan, M. A. H.; Foroni, D.; and Brasche, G. In 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), pages 1115–1122, 2018. IEEE
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VIRTOOAIR: virtual reality toolbox for avatar intelligent reconstruction. Becher, A.; Axenie, C.; and Grauschopf, T. In 2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), pages 275–279, 2018. IEEE
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  2016 (4)
Synthesis of Distributed Cognitive Systems: Interacting Computational Maps for Multisensory Fusion. Axenie, C. Ph.D. Thesis, PhD Thesis, Technische Universität München, 2016.
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A self-synthesis approach to perceptual learning for multisensory fusion in robotics. Axenie, C.; Richter, C.; and Conradt, J. Sensors, 16(10): 1751. 2016.
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From adaptive reasoning to cognitive factory: Bringing cognitive intelligence to manufacturing technology. Sugiarto, I.; Axenie, C.; and Conradt, J. International Journal of Industrial Research and Applied Engineering, 1(1): 1–10. 2016.
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Context-Aware Computing : From Neuroscience to Mobile Devices. Gross, M.; Axenie, C.; and Conradt, J. 2016.
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  2015 (3)
Cortically inspired sensor fusion network for mobile robot egomotion estimation. Axenie, C.; and Conradt, J. Robotics and Autonomous Systems, 71: 69–82. 2015.
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Cognitive maps for indirect coordination of intelligent agents. Susnea, I.; and Axenie, C. Studies in Informatics and Control, 24(1): 111–118. 2015.
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Learning sensory correlations for 3D egomotion estimation. Axenie, C.; and Conradt, J. In Conference on Biomimetic and Biohybrid Systems, pages 329–338, 2015. Springer, Cham
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  2014 (2)
Modulating Neural Activity can bias Neural Dynamics in Attractor Networks for Optimal Weighted Cueing. Firouzi, M.; Axenie, C.; Glasauer, S.; and Conradt, J. In BCCN-Munich Conference, Tutzing, 2014.
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UAV Sound Source Localization. Hausamann, P.; Axenie, C.; and Conradt, J. 2014.
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  2013 (3)
Cortically inspired sensor fusion network for mobile robot heading estimation. Axenie, C.; and Conradt, J. In International Conference on Artificial Neural Networks, pages 240–247, 2013. Springer, Berlin, Heidelberg
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A Flexible Framework for Cue Integration by Line Attraction Dynamics and Divisive Normalization. Firouzi, M.; Axenie, C.; Glasauer, S.; and Conradt, J. In BCCN Sparks workshop, Munich, pages 2–4, 2013.
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Multi-sensory cue integration with reliability encoding, using Line Attractor Dynamics, searching for optimality. Firouzi, M.; Axenie, C.; and Conradt, J. . 2013.
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  2012 (2)
Synthesis of Distributed Cognitive Systems: Interacting Maps for Sensor Fusion. Axenie, C; and Conradt, J In Front. Comput. Neurosci. Conference Abstract: Bernstein Conference, 2012.
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Quadrocopter stabilization using neuromorphic Embedded Dynamic Vision Sensors (eDVS). Bergner, F.; Axenie, C.; and Conradt, J. 2012.
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  2010 (4)
A new approach in mobile robot fault tolerant control: Minimizing costs and extending functionality. Axenie, C. WSEAS Transactions in Systems and Control, 5: 205–216. 2010.
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Adaptive sliding mode controller design for mobile robot fault tolerant control. introducing ARTEMIC. Axenie, C.; and Cernega, D. In 19th International Workshop on Robotics in Alpe-Adria-Danube Region (RAAD 2010), pages 253–259, 2010. IEEE
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Mobile robot fault tolerant control introducing ARTEMIC. Axenie, C.; and Cernega, D. In 2010 2nd International Conference on Education Technology and Computer, volume 5, pages V5–6, 2010. IEEE
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Real time control design for mobile robot fault tolerant control. Introducing the ARTEMIC powered mobile robot. Axenie, C.; and Solea, R. In Proceedings of 2010 IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, pages 7–13, 2010. IEEE
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  2007 (1)
A Client-Server Based Real-Time Control Tool for Complex Distributed Systems. Axenie, C.; Andrei, P.; Florentina, M.; Marius, P.; Aurelian, Z.; and Alexandru, S. In 9th Real-Time Linux Workshop 2007, Embedded Linux Conference Europe 2007, 2007. https://www.osadl.org/fileadmin/events/rtlws-2007/Axenie.pdf
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