Levin Kuhlmann

66 papers A* 1A 1B 2C 2Misc 1Journal 38Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ARROW: Augmented Replay for RObust World models. CoRR Abdulaziz Alyahya, Abdallah Al Siyabi, Markus R. Ernst, Luke Yang, Levin Kuhlmann, Gideon Kowadlo
2026	J	`jnl`	An attributed multiplex network enabled GNN-based stock predictor with observable and non-observable information. Expert Syst. Appl. Zhipeng Liu, Peibo Duan, Qi Chu, Levin Kuhlmann, Changsheng Zhang, Wenwei Yue, Xuan Tang, Bin Zhang
2025	J	`jnl`	Channel-annotated deep learning for enhanced interpretability in EEG-based seizure detection. Biomed. Signal Process. Control. Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien
2025	J	`jnl`	Hi-DREAM: Brain Inspired Hierarchical Diffusion for fMRI Reconstruction via ROI Encoder and visuAl Mapping. CoRR Guowei Zhang, Yun Zhao, Moein Khajehnejad, Adeel Razi, Levin Kuhlmann
2025	A*	`conf`	ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks. IJCAI Kai Sun, Peibo Duan, Levin Kuhlmann, Beilun Wang, Bin Zhang
2025	J	`jnl`	ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks. CoRR Kai Sun, Peibo Duan, Levin Kuhlmann, Beilun Wang, Bin Zhang
2025	—	`conf`	Privacy-Centric Seizure Detection Using Surface Normals, Pose and Segmentation Masks. AI (2) Kishore Gandhi Ponnambalam, Talha Ilyas, Shobi Sivathamboo, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Deval Mehta
2024	Misc	`conf`	A Novel Vision-Based Transformer for Seizure Detection with Multi-biosignals. AusDM Sheng Wong, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien
2024	J	`jnl`	Augmenting Replay in World Models for Continual Reinforcement Learning. CoRR Luke Yang, Levin Kuhlmann, Gideon Kowadlo
2024	C	`conf`	Forecasting events in multidimensional electroencephalographic brain data: Application to epileptic seizure prediction. FUSION Yueyang Liu, Artemio Soto-Breceda, Mark J. Cook, Philippa J. Karoly, David B. Grayden, Levin Kuhlmann, Dean R. Freestone, Daniel Schmidt
2024	—	`conf`	Graceful Task Adaptation with a Bi-hemispheric RL Agent. AI (2) Grant Nicholas, Levin Kuhlmann, Gideon Kowadlo
2024	J	`jnl`	Graceful task adaptation with a bi-hemispheric RL agent. CoRR Grant Nicholas, Levin Kuhlmann, Gideon Kowadlo
2024	C	`conf`	Inference-based time-resolved chaos analysis of brain models: application to focal epilepsy. FUSION Yun Zhao, David B. Grayden, Mario Boley, Yueyang Liu, Philippa J. Karoly, Mark J. Cook, Levin Kuhlmann
2024	—	`conf`	Left/Right Brain, Human Motor Control and the Implications for Robotics. LOD (3) Jarrad Rinaldo, Jason Friedman, Levin Kuhlmann, Gideon Kowadlo
2024	J	`jnl`	Left/Right Brain, human motor control and the implications for robotics. CoRR Jarrad Rinaldo, Levin Kuhlmann, Jason Friedman, Gideon Kowadlo
2024	A	`conf`	Measuring Affective and Motivational States as Conditions for Cognitive and Metacognitive Processing in Self-Regulated Learning. LAK Mladen Rakovic, Yuheng Li, Navid Mohammadi Foumani, Mahsa Salehi, Levin Kuhlmann, Geoffrey Mackellar, Roberto Martínez Maldonado, Gholamreza Haffari, Zachari Swiecki, Xinyu Li, Guanliang Chen, Dragan Gasevic
2024	J	`jnl`	Uncovering co-regulatory modules and gene regulatory networks in the heart through machine learning-based analysis of large-scale epigenomic data. Comput. Biol. Medicine Naima Vahab, Tarun Bonu, Levin Kuhlmann, Mirana Ramialison, Sonika Tyagi
2023	J	`jnl`	Automated Interictal Epileptiform Discharge Detection from Scalp EEG Using Scalable Time-series Classification Approaches. Int. J. Neural Syst. D. Nhu, M. Janmohamed, L. Shakhatreh, O. Gonen, Piero Perucca, A. Gilligan, Patrick Kwan, Terence J. O'Brien, Chang Wei Tan, Levin Kuhlmann
2023	J	`jnl`	Brain Model State Space Reconstruction Using an LSTM Neural Network. CoRR Yueyang Liu, Artemio Soto-Breceda, Yun Zhao, Phillipa Karoly, Mark J. Cook, David B. Grayden, Daniel Schmidt, Levin Kuhlmann
2023	J	`jnl`	Improved Neurophysiological Process Imaging Through Optimization of Kalman Filter Initial Conditions. Int. J. Neural Syst. Yun Zhao, Felix Luong, Simon Teshuva, Andria Pelentritou, William Woods, David T. J. Liley, Daniel F. Schmidt, Mario Boley, Levin Kuhlmann
2023	—	`conf`	Inference-based time-resolved stability analysis of nonlinear whole-cortex modeling: application to Xenon anaesthesia. EMBC Yun Zhao, Mario Boley, Andria Pelentritou, William Woods, David T. J. Liley, Levin Kuhlmann
2023	—	`conf`	Model Parameter Estimation As Features to Predict the Duration of Epileptic Seizures From Onset. EMBC Yueyang Liu, Siqi Xia, Artemio Soto-Breceda, Philippa J. Karoly, Mark J. Cook, David B. Grayden, Daniel Schmidt, Levin Kuhlmann
2022	—	`conf`	Deep Learning Models for Seizure Prediction using the Wavelet Transform. ICM Yasmin M. Massoud, Mennatallah Sherif, Levin Kuhlmann, Mohamed A. Abd El Ghany
2022	—	`conf`	Enhanced Extra Trees Classifier for Epileptic Seizure Prediction. ICSPIS Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi
2022	—	`conf`	FPGA Implementation of Epileptic Seizure Detection using Artificial Neural Network. NILES Ahmad A. Ahmad, Yasmin M. Massoud, Levin Kuhlmann, Mohamed A. Abd El Ghany
2022	J	`jnl`	Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps. Sensors Chuen Rue Ng, Patrique Fiedler, Levin Kuhlmann, David T. J. Liley, Beatriz Vasconcelos, Carlos Fonseca, Gabriella Tamburro, Silvia Comani, Troby Ka-Yan Lui, Chun-Yu Tse, Indhika Fauzhan Warsito, Eko Supriyanto, Jens Haueisen
2022	—	`conf`	Predicting epileptic seizures from raw EEG signals using advanced deep learning techniques. NILES Mohamed Gamil, Yasmin M. Massoud, Levin Kuhlmann, Mohamed A. Abd El Ghany
2022	J	`jnl`	Space-time resolved inference-based neurophysiological process imaging: Application to resting-state alpha rhythm. NeuroImage Yun Zhao, Mario Boley, Andria Pelentritou, Philippa J. Karoly, Dean R. Freestone, Yueyang Liu, Suresh D. Muthukumaraswamy, William Woods, David T. J. Liley, Levin Kuhlmann
2021	B	`conf`	A Multimodal Dataset and Evaluation for Feature Estimators of Temporal Phases of Anxiety. ICMI Hashini Senaratne, Levin Kuhlmann, Kirsten Ellis, Glenn Melvin, Sharon L. Oviatt
2021	—	`conf`	A Two-Layer LSTM Deep Learning Model for Epileptic Seizure Prediction. AICAS Shiva Maleki Varnosfaderani, Rihat Rahman, Nabil J. Sarhan, Levin Kuhlmann, Eishi Asano, Aimee F. Luat, Mohammad Alhawari
2021	J	`jnl`	Coherent False Seizure Prediction in Epilepsy, Coincidence or Providence? CoRR Jens Müller, Hongliu Yang, Matthias Eberlein, Georg Leonhardt, Ortrud Uckermann, Levin Kuhlmann, Ronald Tetzlaff
2021	—	`conf`	Comparison of Patient Specific and General Classification of Epileptic Seizure Prediction. ICM Yasmin M. Massoud, Levin Kuhlmann, Mohamed A. Abd El Ghany
2021	—	`conf`	Evaluation of Channel Performance in Seizure Prediction. ACSW Hoai An Nguyen, Zhinoos Razavi Hesabi, Levin Kuhlmann
2020	J	`jnl`	A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction. CoRR Khansa Rasheed, Junaid Qadir, Terence J. O'Brien, Levin Kuhlmann, Adeel Razi
2020	—	`conf`	Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees. ACSW Sheng Wong, Levin Kuhlmann
2020	—	`conf`	Epileptic Seizure Detection Using Convolutional Neural Network: A Multi-Biosignal study. ACSW Yu Liu, Shobi Sivathamboo, Peter Goodin, C. Paul Bonnington, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien, Piero Perucca, Zongyuan Ge
2020	J	`jnl`	Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review. CoRR Khansa Rasheed, Adnan Qayyum, Junaid Qadir, Shobi Sivathamboo, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien, Adeel Razi
2020	—	`conf`	Self-organising Neural Network Hierarchy. Australasian Conference on Artificial Intelligence Satya Borgohain, Gideon Kowadlo, David Rawlinson, Christoph Bergmeir, Kok Loo, Harivallabha Rangarajan, Levin Kuhlmann
2020	J	`jnl`	Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA). Comput. Biol. Medicine Yashpal Ramakrishnaiah, Levin Kuhlmann, Sonika Tyagi
2019	J	`jnl`	Epileptic Seizure Forecasting With Generative Adversarial Networks. IEEE Access Nhan Duy Truong, Levin Kuhlmann, Mohammad Reza Bonyadi, Damien Querlioz, Luping Zhou, Omid Kavehei
2019	J	`jnl`	Human Intracranial EEG Quantitative Analysis and Automatic Feature Learning for Epileptic Seizure Prediction. CoRR Ramy Hussein, Mohamed Osama Ahmed, Rabab Ward, Z. Jane Wang, Levin Kuhlmann, Yi Guo
2018	—	`conf`	Convolutional Neural Networks for Epileptic Seizure Prediction. BIBM Matthias Eberlein, Raphael Hildebrand, Ronald Tetzlaff, Nico Hoffmann, Levin Kuhlmann, Benjamin H. Brinkmann, Jens Müller
2018	J	`jnl`	Convolutional Neural Networks for Epileptic Seizure Prediction. CoRR Matthias Eberlein, Raphael Hildebrand, Ronald Tetzlaff, Nico Hoffmann, Levin Kuhlmann, Benjamin H. Brinkmann, Jens Müller
2018	J	`jnl`	Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram. Neural Networks Nhan Duy Truong, Anh Duy Nguyen, Levin Kuhlmann, Mohammad Reza Bonyadi, Jiawei Yang, Samuel J. Ippolito, Omid Kavehei
2018	J	`jnl`	Integer Convolutional Neural Network for Seizure Detection. IEEE J. Emerg. Sel. Topics Circuits Syst. Nhan Duy Truong, Anh Duy Nguyen, Levin Kuhlmann, Mohammad Reza Bonyadi, Jiawei Yang, Samuel James Ippolito, Omid Kavehei
2018	J	`jnl`	Seizure pathways: A model-based investigation. PLoS Comput. Biol. Philippa J. Karoly, Levin Kuhlmann, Daniel Soudry, David B. Grayden, Mark J. Cook, Dean R. Freestone
2018	J	`jnl`	Semi-supervised Seizure Prediction with Generative Adversarial Networks. CoRR Nhan Duy Truong, Levin Kuhlmann, Mohammad Reza Bonyadi, Omid Kavehei
2017	J	`jnl`	A Generalised Seizure Prediction with Convolutional Neural Networks for Intracranial and Scalp Electroencephalogram Data Analysis. CoRR Nhan Duy Truong, Anh Duy Nguyen, Levin Kuhlmann, Mohammad Reza Bonyadi, Jiawei Yang, Omid Kavehei
2017	J	`jnl`	Introduction. Int. J. Neural Syst. Levin Kuhlmann, David B. Grayden, Mark J. Cook
2017	J	`jnl`	Probing to Observe Neural Dynamics Investigated with Networked Kuramoto Oscillators. Int. J. Neural Syst. Elma O'Sullivan-Greene, Levin Kuhlmann, Ewan Nurse, Dean R. Freestone, David B. Grayden, Mark J. Cook, Anthony N. Burkitt, Iven Mareels
2017	J	`jnl`	Statistical Performance Analysis of Data-Driven Neural Models. Int. J. Neural Syst. Dean R. Freestone, Kelvin J. Layton, Levin Kuhlmann, Mark J. Cook
2017	J	`jnl`	Supervised Learning in Automatic Channel Selection for Epileptic Seizure Detection. CoRR Nhan Duy Truong, Levin Kuhlmann, Mohammad Reza Bonyadi, Jiawei Yang, Andrew Faulks, Omid Kavehei
2017	J	`jnl`	Supervised learning in automatic channel selection for epileptic seizure detection. Expert Syst. Appl. Nhan Duy Truong, Levin Kuhlmann, Mohammad Reza Bonyadi, Jiawei Yang, Andrew Faulks, Omid Kavehei
2017	J	`jnl`	Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring. IEEE Trans. Biomed. Eng. Levin Kuhlmann, Jonathan H. Manton, Bjorn Heyse, Hugo E. M. Vereecke, Tarmo Lipping, Michel M. R. F. Struys, David T. J. Liley
2016	J	`jnl`	Neural mass model-based tracking of anesthetic brain states. NeuroImage Levin Kuhlmann, Dean R. Freestone, Jonathan H. Manton, Bjorn Heyse, Hugo E. M. Vereecke, Tarmo Lipping, Michel M. R. F. Struys, David T. J. Liley
2015	J	`jnl`	Parameter and State Estimation of Nonlinear Systems Using a Multi-Observer Under the Supervisory Framework. IEEE Trans. Autom. Control. Michelle S. Chong, Dragan Nesic, Romain Postoyan, Levin Kuhlmann
2014	J	`jnl`	Approximate, Computationally Efficient Online Learning in Bayesian Spiking Neurons. Neural Comput. Levin Kuhlmann, Michael Hauser-Raspe, Jonathan H. Manton, David B. Grayden, Jonathan Tapson, André van Schaik
2014	J	`jnl`	Observability limits for networked oscillators. Autom. Elma O'Sullivan-Greene, Iven Mareels, Levin Kuhlmann, Anthony N. Burkitt
2014	—	`conf`	State and parameter estimation of nonlinear systems: A multi-observer approach. CDC Michelle S. Chong, Dragan Nesic, Romain Postoyan, Levin Kuhlmann
2012	J	`jnl`	A robust circle criterion observer with application to neural mass models. Autom. Michelle Chong, Romain Postoyan, Dragan Nesic, Levin Kuhlmann, Andrea Varsavsky
2012	B	`conf`	Online learning in Bayesian Spiking Neurons. IJCNN Levin Kuhlmann, Michael Hauser-Raspe, Jonathan H. Manton, David B. Grayden, Jonathan Tapson, André van Schaik
2012	—	`conf`	Parameter and state estimation for a class of neural mass models. CDC Romain Postoyan, Michelle Chong, Dragan Nesic, Levin Kuhlmann
2011	—	`conf`	A circle criterion observer for estimating the unmeasured membrane potential of neuronal populations. AuCC Michelle Chong, Romain Postoyan, Dragan Nesic, Levin Kuhlmann, Andrea Varsavsky
2011	—	`conf`	Probing for cortical excitability. EMBC Dean R. Freestone, Anthony N. Burkitt, Alan Lai, Timothy S. Nelson, David B. Grayden, Simon J. Vogrin, Michael Murphy, Wendyl D'Souza, Radwa A. B. Badawy, Levin Kuhlmann, Mark J. Cook
2009	—	`conf`	Observability issues in networked clocks with applications to epilepsy. CDC Elma O'Sullivan-Greene, Iven M. Y. Mareels, Anthony N. Burkitt, Levin Kuhlmann
2002	J	`jnl`	Summation of Spatiotemporal Input Patterns in Leaky Integrate-and-Fire Neurons: Application to Neurons in the Cochlear Nucleus Receiving Converging Auditory Nerve Fiber Input. J. Comput. Neurosci. Levin Kuhlmann, Anthony N. Burkitt, Antonio Paolini, Graeme M. Clark