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ORCIDChristian W. Omlin
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- affiliation: University of Agder, Grimstad, Norway
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2020 – today
- 2024
[c36]Martin Holen
, Jayant Singh, Christian W. Omlin, Jing Zhou, Kristian Muri Knausgård, Morten Goodwin:
Optimizing Autonomous Vehicle Racing Using Reinforcement Learning with Pre-trained Embeddings for Dimensionality Reduction. SGAI Conf. (2) 2024: 21-34- [c35]Ajay Vishwanath, Christian W. Omlin:
Localized Affinity-Based Reinforcement Learning for Interpretable State-Specific Decision-Making. SGAI Conf. (1) 2024: 221-234 - [i16]Mulugeta Weldezgina Asres, Christian Walter Peter Omlin, Jay Dittmann, Pavel Parygin, Joshua Hiltbrand, Seth I. Cooper, Grace Cummings, David Yu:
Lightweight Multi-System Multivariate Interconnection and Divergence Discovery. CoRR abs/2404.08453 (2024) - [i15]Mulugeta Weldezgina Asres, Christian Walter Peter Omlin, Long Wang, Pavel Parygin, David Yu, Jay Dittmann, the CMS-HCAL Collaboration:
Data Quality Monitoring through Transfer Learning on Anomaly Detection for the Hadron Calorimeters. CoRR abs/2408.16612 (2024) - [i14]Mulugeta Weldezgina Asres, Lei Jiao, Christian W. Omlin:
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy vs. Performance. CoRR abs/2410.18717 (2024) - 2023
- [j17]Ajay Vishwanath, Einar Duenger Bøhn, Ole-Christoffer Granmo, Charl Maree, Christian W. Omlin:
Towards artificial virtuous agents: games, dilemmas and machine learning. AI Ethics 3(3): 663-672 (2023) - [j16]Micheal Dutt, Surender Redhu, Morten Goodwin, Christian W. Omlin:
SleepXAI: An explainable deep learning approach for multi-class sleep stage identification. Appl. Intell. 53(13): 16830-16843 (2023) - [j15]Wahiba Bounoua, Muhammad Faisal Aftab, Christian Walter Peter Omlin:
Online detrended fluctuation analysis and improved empirical wavelet transform for real-time oscillations detection in industrial control loops. Comput. Chem. Eng. 172: 108173 (2023) - [j14]Waddah Saeed, Christian W. Omlin:
Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities. Knowl. Based Syst. 263: 110273 (2023) - [j13]Md. Haidar Sharif, Lei Jiao, Christian W. Omlin:
CNN-ViT Supported Weakly-Supervised Video Segment Level Anomaly Detection. Sensors 23(18): 7734 (2023) - [j12]Mulugeta Weldezgina Asres, Christian Walter Peter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, Georgia Karapostoli, Markus Seidel, Rosamaria Venditti, Luka Lambrecht, Emanuele Usai, Muhammad Ahmad, Javier Fernandez Menendez, Kaori Maeshima, the CMS-HCAL Collaboration:
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter. Sensors 23(24): 9679 (2023) - [c34]Michal Darowski, Muhammad Faisal Aftab, Hongyu Li, David Walker, Guoyu Yu, Chenghui An, Christian W. Omlin:
Towards Data-Driven Material Removal Rate Estimation in Bonnet Polishing. ICCMA 2023: 473-479 - [c33]Touseef Sadiq, Christian W. Omlin:
Scene Retrieval in Traffic Videos with Contrastive Multimodal Learning. ICTAI 2023: 1020-1025 - [i13]Muriel Figueredo Franco, Christian W. Omlin, Oliver Kamer, Eder John Scheid, Burkhard Stiller:
SECAdvisor: a Tool for Cybersecurity Planning using Economic Models. CoRR abs/2304.07909 (2023) - [i12]Mulugeta Weldezgina Asres, Christian Walter Peter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, Georgia Karapostoli, Markus Seidel, Rosamaria Venditti, Luka Lambrecht, Emanuele Usai, Muhammad Ahmad, Javier Fernandez Menendez, Kaori Maeshima:
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter. CoRR abs/2311.04190 (2023) - 2022
- [c32]Charl Maree, Christian W. Omlin:
Balancing Profit, Risk, and Sustainability for Portfolio Management. CIFEr 2022: 1-8 - [c31]Charl Maree, Christian W. Omlin:
Understanding Spending Behavior: Recurrent Neural Network Explanation and Interpretation. CIFEr 2022: 1-7 - [c30]Micheal Dutt, Surender Redhu, Morten Goodwin, Christian W. Omlin:
Sleep Stage Identification based on Single-Channel EEG Signals using 1-D Convolutional Autoencoders. HealthCom 2022: 94-99 - [i11]Charl Maree, Christian W. Omlin:
Reinforcement Learning Your Way: Agent Characterization through Policy Regularization. CoRR abs/2201.10003 (2022) - [i10]Charl Maree, Christian W. Omlin:
Can Interpretable Reinforcement Learning Manage Assets Your Way? CoRR abs/2202.09064 (2022) - [i9]Charl Maree, Christian W. Omlin:
Reinforcement Learning with Intrinsic Affinity for Personalized Asset Management. CoRR abs/2204.09218 (2022) - [i8]Charl Maree, Jan Erik Modal, Christian W. Omlin:
Towards Responsible AI for Financial Transactions. CoRR abs/2206.02419 (2022) - [i7]Charl Maree, Christian W. Omlin:
Balancing Profit, Risk, and Sustainability for Portfolio Management. CoRR abs/2207.02134 (2022) - [i6]Charl Maree, Christian W. Omlin:
Symbolic Explanation of Affinity-Based Reinforcement Learning Agents with Markov Models. CoRR abs/2208.12627 (2022) - [i5]Md. Haidar Sharif, Lei Jiao, Christian W. Omlin:
Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions. CoRR abs/2210.13927 (2022) - 2021
- [c29]Micheal Dutt, Morten Goodwin, Christian W. Omlin:
Automatic Sleep Stage Identification with Time Distributed Convolutional Neural Network. IJCNN 2021: 1-7 - [c28]Charl Maree, Christian W. Omlin:
Clustering in Recurrent Neural Networks for Micro-Segmentation using Spending Personality. SSCI 2021: 1-5 - [i4]Charl Maree, Christian W. Omlin:
Clustering in Recurrent Neural Networks for Micro-Segmentation using Spending Personality. CoRR abs/2109.09425 (2021) - [i3]Charl Maree, Christian W. Omlin:
Discovering Novel Customer Features with Recurrent Neural Networks for Personality Based Financial Services. CoRR abs/2109.11871 (2021) - [i2]Waddah Saeed, Christian W. Omlin:
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities. CoRR abs/2111.06420 (2021) - 2020
- [c27]Martin Holen, Rupsa Saha, Morten Goodwin, Christian W. Omlin, Knut Eivind Sandsmark:
Road Detection for Reinforcement Learning Based Autonomous Car. ICISS 2020: 67-71 - [c26]Charl Maree, Jan Erik Modal, Christian W. Omlin:
Towards Responsible AI for Financial Transactions. SSCI 2020: 16-21
2010 – 2019
- 2019
- [i1]Ole-Christoffer Granmo, Sondre Glimsdal, Lei Jiao, Morten Goodwin, Christian W. Omlin, Geir Thore Berge:
The Convolutional Tsetlin Machine. CoRR abs/1905.09688 (2019) - 2016
- [c25]Rohitash Chandra, Ratneel Deo, Christian W. Omlin:
An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks. IJCNN 2016: 4865-4872 - 2014
- [j11]Ralf C. Staudemeyer, Christian W. Omlin:
Extracting salient features for network intrusion detection using machine learning methods. South Afr. Comput. J. 52: 82-96 (2014) - [c24]Deniz Bingol, Turgay Çelik, Christian W. Omlin, Hima B. Vadapalli:
Facial action unit intensity estimation using rotation invariant features and regression analysis. ICIP 2014: 1381-1385 - 2013
- [c23]Ralf C. Staudemeyer, Christian W. Omlin:
Evaluating performance of long short-term memory recurrent neural networks on intrusion detection data. SAICSIT 2013: 218-224 - 2011
- [j10]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang, Christian W. Omlin:
Encoding subcomponents in cooperative co-evolutionary recurrent neural networks. Neurocomputing 74(17): 3223-3234 (2011)
2000 – 2009
- 2009
- [c22]Hima Vadapalli, Henry O. Nyongesa, Christian W. Omlin:
Facial Action Unit Recognition Using Recurrent Neural Networks. IPCV 2009: 357-361 - [p1]Bénard Wiese, Christian W. Omlin:
Credit Card Transactions, Fraud Detection, and Machine Learning: Modelling Time with LSTM Recurrent Neural Networks. Innovations in Neural Information Paradigms and Applications 2009: 231-268 - 2008
- [c21]Rohitash Chandra, Christian W. Omlin:
Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent Neural Networks. GEM 2008: 305-311 - 2007
- [c20]Rohitash Chandra, Christian W. Omlin:
A Hybrid Recurrent Neural Networks Architecture Inspired by Hidden Markov Models: Training and Extraction of Deterministic Finite Automaton. Artificial Intelligence and Pattern Recognition 2007: 278-285 - [c19]Rohitash Chandra, Christian W. Omlin:
The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification. Artificial Intelligence and Pattern Recognition 2007: 286-293 - [c18]Rohitash Chandra, Christian W. Omlin:
Knowledge Discovery using Artificial Neural Networks for a Conservation Biology Domain. DMIN 2007: 221-227 - [c17]Rohitash Chandra, Christian W. Omlin:
Hybrid Recurrent Neural Networks: An Application to Phoneme Classification. GEM 2007: 57-62 - 2006
- [c16]Jacob Whitehill, Christian W. Omlin:
Haar Features for FACS AU Recognition. FGR 2006: 97-101 - [c15]Jacob Whitehill, Christian W. Omlin:
Local versus Global Segmentation for Facial Expression Recognition. FGR 2006: 357-362 - [c14]Rohitash Chandra, Christian W. Omlin:
Training and extraction of fuzzy finite state automata in recurrent neural networks. Computational Intelligence 2006: 274-279 - [c13]Okuthe Paul Kogeda, Johnson I. Agbinya, Christian W. Omlin:
A Probabilistic Approach To Faults Prediction in Cellular Networks. ICN/ICONS/MCL 2006: 130 - 2005
- [c12]Okuthe Paul Kogeda, Johnson I. Agbinya, Christian W. Omlin:
Impacts and Cost of Faults on Services in Cellular Networks. ICMB 2005: 551-555 - 2004
- [j9]A. Vahed, Christian W. Omlin:
A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks. Neural Comput. 16(1): 59-71 (2004) - 2003
- [j8]Christian W. Omlin, Sean Snyders:
Inductive bias strength in knowledge-based neural networks: application to magnetic resonance spectroscopy of breast tissues. Artif. Intell. Medicine 28(2): 121-140 (2003) - 2002
- [c11]Dane Walsh, Christian W. Omlin:
Automatic Detection of Film Orientation with Support Vector Machines. IEA/AIE 2002: 36-46 - 2001
- [c10]Sean Snyders, Christian W. Omlin:
Inductive Bias in Recurrent Neural Networks. IWANN (1) 2001: 339-346 - [c9]Jacobus van Zyl, Christian W. Omlin:
Knowledge-Based Neural Networks for Modelling Time Series. IWANN (2) 2001: 579-586 - 2000
- [c8]Andries Kruger, C. Lee Giles, Frans Coetzee, Eric J. Glover, Gary William Flake, Steve Lawrence, Christian W. Omlin:
DEADLINER: Building a New Niche Search Engine. CIKM 2000: 272-281 - [c7]T. Wessels, Christian W. Omlin:
Refining Hidden Markov Models with Recurrent Neural Networks. IJCNN (2) 2000: 271-278 - [c6]Sean Snyders, Christian W. Omlin:
What Inductive Bias Gives Good Neural Network Training Performance? IJCNN (3) 2000: 445-450 - [c5]T. Wessels, Christian W. Omlin:
A Hybrid System for Signature Verification. IJCNN (5) 2000: 509-514
1990 – 1999
- 1999
- [j7]C. Lee Giles, Christian W. Omlin, Karvel K. Thornber:
Equivalence in knowledge representation: automata, recurrent neural networks, and dynamical fuzzy systems. Proc. IEEE 87(9): 1623-1640 (1999) - 1998
- [j6]Christian W. Omlin, Karvel K. Thornber, Clyde Lee Giles:
Fuzzy finite-state automata can be deterministically encoded into recurrent neural networks. IEEE Trans. Fuzzy Syst. 6(1): 76-89 (1998) - [c4]Christian W. Omlin, C. Lee Giles, Karvel K. Thornber:
Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective. Hybrid Neural Systems 1998: 123-143 - 1996
- [j5]Christian W. Omlin, C. Lee Giles:
Constructing Deterministic Finite-State Automata in Recurrent Neural Networks. J. ACM 43(6): 937-972 (1996) - [j4]Christian W. Omlin, C. Lee Giles:
Stable encoding of large finite-state automata in recurrent neural networks with sigmoid discriminants. Neural Comput. 8(4): 675-696 (1996) - [j3]Christian W. Omlin, C. Lee Giles:
Extraction of rules from discrete-time recurrent neural networks. Neural Networks 9(1): 41-52 (1996) - [j2]Christian W. Omlin, C. Lee Giles:
Rule Revision With Recurrent Neural Networks. IEEE Trans. Knowl. Data Eng. 8(1): 183-188 (1996) - [c3]Christian W. Omlin, Karvel K. Thornber, C. Lee Giles:
Representation of fuzzy finite state automata in continuous recurrent, neural networks. ICNN 1996: 1023-1027 - 1994
- [b1]Christian W. Omlin:
Symbolic information in recurrent neural networks: Issues of representation and training. Rensselaer Polytechnic Institute, USA, 1994 - [j1]C. Lee Giles, Christian W. Omlin:
Pruning recurrent neural networks for improved generalization performance. IEEE Trans. Neural Networks 5(5): 848-851 (1994) - 1993
- [c2]C. Lee Giles, Christian W. Omlin:
Rule refinement with recurrent neural networks. ICNN 1993: 801-806 - 1992
- [c1]Christian W. Omlin, C. Lee Giles:
Training Second-Order Recurrent Neural Networks using Hints. ML 1992: 361-366
Coauthor Index
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