Thomas Trappenberg

91 papers A* 1B 26C 1Misc 1Journal 40Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Beyond the Black Box: A Heuristic-Based Framework for Employing Real-World Reasoning towards Explainable and Reliable Results. VISAPP (1) Murilo Santos Regio, Thomas Trappenberg, Isabel H. Manssour
2026	J	`jnl`	Improving Detection of Rare Nodes in Hierarchical Multi-Label Learning. CoRR Isaac Xu, Martin Gillis, Ayushi Sharma, Benjamin Misiuk, Craig J. Brown, Thomas Trappenberg
2026	J	`jnl`	Improving Detection of Rare Nodes in Hierarchical Multi-Label Learning. Trans. Mach. Learn. Res. Isaac Xu, Martin Gillis, Ayushi Sharma, Benjamin Misiuk, Craig J. Brown, Thomas Trappenberg
2026	J	`jnl`	Last-layer committee machines for uncertainty estimations of benthic imagery. Neural Networks Martin Gillis, Isaac Xu, Benjamin Misiuk, Craig J. Brown, Thomas Trappenberg
2026	J	`jnl`	Variance-Gated Ensembles: An Epistemic-Aware Framework for Uncertainty Estimation. CoRR Martin Gillis, Isaac Xu, Thomas Trappenberg
2025	B	`conf`	Masked strategies for images with small objects. IJCNN Martin Gillis, Ming Hill, Paul Hollensen, Alan Fine, Thomas Trappenberg
2025	J	`jnl`	Masked strategies for images with small objects. CoRR Martin Gillis, Ming Hill, Paul Hollensen, Alan Fine, Thomas Trappenberg
2025	J	`jnl`	Platelet enumeration in dense aggregates. CoRR Martin Gillis, Yogeshwar Shendye, Paul Hollensen, Alan Fine, Thomas Trappenberg
2025	B	`conf`	Position paper: Foundation models are not the brain. IJCNN Thomas Trappenberg
2025	—	`conf`	Pupillometry for Arm and Hand Motor Intent Detection. ICORR Shane Forbrigger, Thomas Trappenberg, Ya-Jun Pan
2025	J	`jnl`	Uncertainty Estimation using Variance-Gated Distributions. CoRR Martin Gillis, Isaac Xu, Thomas Trappenberg
2024	J	`jnl`	A Generalized Transformer-based Radio Link Failure Prediction Framework in 5G RANs. CoRR Kazi Hasan, Thomas Trappenberg, Israat Haque
2024	J	`jnl`	An Information-Geometric Formulation of Pattern Separation and Evaluation of Existing Indices. Entropy Harvey Wang, Selena Singh, Thomas Trappenberg, Abraham Nunes
2024	J	`jnl`	BenthicNet: A global compilation of seafloor images for deep learning applications. CoRR Scott C. Lowe, Benjamin Misiuk, Isaac Xu, Shakhboz Abdulazizov, Amit R. Baroi, Alex C. Bastos, Merlin Best, Vicki Ferrini, Ariell Friedman, Deborah Hart, Ove Hoegh-Guldberg, Daniel Ierodiaconou, Julia Mackin-McLaughlin, Kathryn Markey, Pedro S. Menandro, Jacquomo Monk, Shreya Nemani, John O'Brien, Elizabeth S. Oh, Luba Y. Reshitnyk, Katleen Robert, Chris M. Roelfsema, Jessica A. Sameoto, Alexandre C. G. Schimel, Jordan A. Thomson, Brittany R. Wilson, Melisa C. Wong, Craig J. Brown, Thomas Trappenberg
2024	B	`conf`	Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery. IJCNN Isaac Xu, Benjamin Misiuk, Scott C. Lowe, Martin Gillis, Thomas Trappenberg, Craig J. Brown
2024	J	`jnl`	Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery. CoRR Isaac Xu, Benjamin Misiuk, Scott C. Lowe, Martin Gillis, Craig J. Brown, Thomas Trappenberg
2024	J	`jnl`	Label-free Monitoring of Self-Supervised Learning Progress. CoRR Isaac Xu, Scott C. Lowe, Thomas Trappenberg
2022	—	`conf`	Label-free Monitoring of Self-Supervised Learning Progress. CCECE Isaac Xu, Scott C. Lowe, Thomas Trappenberg
2022	A*	`conf`	Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators. NeurIPS Scott C. Lowe, Robert Earle, Jason d'Eon, Thomas Trappenberg, Sageev Oore
2021	J	`jnl`	LogAvgExp Provides a Principled and Performant Global Pooling Operator. CoRR Scott C. Lowe, Thomas Trappenberg, Sageev Oore
2021	J	`jnl`	Logical Activation Functions: Logit-space equivalents of Boolean Operators. CoRR Scott C. Lowe, Robert Earle, Jason d'Eon, Thomas Trappenberg, Sageev Oore
2020	B	`conf`	Learning dynamic weights for an ensemble of deep models applied to medical imaging classification. IJCNN André G. C. Pacheco, Thomas Trappenberg, Renato A. Krohling
2020	J	`jnl`	Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions. Entropy Abraham Nunes, Martin Alda, Thomas Trappenberg
2020	—	`conf`	On Out-of-Distribution Detection Algorithms with Deep Neural Skin Cancer Classifiers. CVPR Workshops André G. C. Pacheco, Chandramouli Shama Sastry, Thomas Trappenberg, Sageev Oore, Renato A. Krohling
2020	J	`jnl`	Representational Rényi Heterogeneity. Entropy Abraham Nunes, Martin Alda, Timothy Bardouille, Thomas Trappenberg
2019	B	`conf`	A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images. IJCNN Abder-Rahman Ali, Jingpeng Li, Sally Jane O'Shea, Guang Yang, Thomas Trappenberg, Xujiong Ye
2019	J	`jnl`	A Novel Model for Arbitration Between Planning and Habitual Control Systems. Frontiers Neurorobotics Farzaneh Sheikhnezhad Fard, Thomas Trappenberg
2019	B	`conf`	Learning Adaptive Weight Masking for Adversarial Examples. IJCNN Yoshimasa Kubo, Michael Traynor, Thomas Trappenberg, Sageev Oore
2019	—	`conf`	Mitigating Overfitting Using Regularization to Defend Networks Against Adversarial Examples. Canadian AI Yoshimasa Kubo, Thomas Trappenberg
2019	J	`jnl`	Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study. Comput. Medical Imaging Graph. Peter Q. Lee, Alessandro Guida, Steve Patterson, Thomas Trappenberg, Chris V. Bowen, Steven D. Beyea, Jennifer Merrimen, Cheng Wang, Sharon E. Clarke
2019	J	`jnl`	Representational Rényi heterogeneity. CoRR Abraham Nunes, Martin Alda, Timothy Bardouille, Thomas Trappenberg
2019	—	`conf`	Self-training for Cell Segmentation and Counting. Canadian AI Junliang Luo, Sageev Oore, Paul Hollensen, Alan Fine, Thomas Trappenberg
2019	J	`jnl`	Skin cancer detection based on deep learning and entropy to detect outlier samples. CoRR André G. C. Pacheco, Abder-Rahman Ali, Thomas Trappenberg
2019	—	`conf`	Supervised Versus Unsupervised Deep Learning Based Methods for Skin Lesion Segmentation in Dermoscopy Images. Canadian AI Abder-Rahman Ali, Jingpeng Li, Thomas Trappenberg
2019	J	`jnl`	Topographic representation adds robustness to supervised learning. J. Intell. Fuzzy Syst. Pitoyo Hartono, Thomas Trappenberg
2019	—	`conf`	Using a Deep CNN for Automatic Classification of Sleep Spindles: A Preliminary Study. Canadian AI Francesco Usai, Thomas Trappenberg
2018	B	`conf`	Mixing Habits and Planning for Multi-Step Target Reaching Using Arbitrated Predictive Actor-Critic. IJCNN Farzaneh Sheikhnezhad Fard, Thomas Trappenberg
2018	B	`conf`	Words Are Not Temporal Sequences of Characters. IJCNN Michael Traynor, Thomas Trappenberg
2017	J	`jnl`	A Novel Model for Arbitration between Planning and Habitual Control Systems. CoRR Farzaneh Sheikhnezhad Fard, Thomas Trappenberg
2017	B	`conf`	Impact of biased mislabeling on learning with deep networks. IJCNN Farzaneh Sheikhnezhad Fard, Paul Hollensen, Stuart McIlroy, Thomas Trappenberg
2017	B	`conf`	In vivo classification of inflammation in blood vessels with convolutional neural networks. IJCNN Stuart McIlroy, Yoshimasa Kubo, Thomas Trappenberg, James Toguri, Christian Lehmann
2016	Misc	`conf`	A Neural Field Approach to Obstacle Avoidance. KI Chun Kwang Tan, Paul G. Plöger, Thomas Trappenberg
2015	J	`jnl`	A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO. Neural Networks Patrick C. Connor, Paul Hollensen, Olav E. Krigolson, Thomas Trappenberg
2015	—	`conf`	Classifier with Hierarchical Topographical Maps as Internal Representation. ICLR (Workshop) Pitoyo Hartono, Paul Hollensen, Thomas Trappenberg
2015	J	`jnl`	Detection of event-related potentials in individual subjects using support vector machines. Brain Informatics Hossein Parvar, Lauren D. Sculthorpe-Petley, Jason Satel, Rober Boshra, Ryan C. N. D'Arcy, Thomas Trappenberg
2015	J	`jnl`	Learning-Regulated Context Relevant Topographical Map. IEEE Trans. Neural Networks Learn. Syst. Pitoyo Hartono, Paul Hollensen, Thomas Trappenberg
2015	J	`jnl`	Modeling human target reaching with an adaptive observer implemented with dynamic neural fields. Neural Networks Farzaneh Sheikhnezhad Fard, Paul Hollensen, Dietmar Heinke, Thomas Trappenberg
2014	—	`ch.`	A Brief Introduction to Probabilistic Machine Learning and Its Relation to Neuroscience. Growing Adaptive Machines Thomas Trappenberg
2014	—	`conf`	An Architecture for Distinguishing between Predictors and Inhibitors in Reinforcement Learning. ICLR (Workshop Poster) Patrick C. Connor, Thomas Trappenberg
2014	J	`jnl`	Simulating oculomotor inhibition of return with a two-dimensional dynamic neural field model of the superior colliculus. Aust. J. Intell. Inf. Process. Syst. Jason Satel, Farzaneh Sheikhnezhad Fard, Zhiguo Wang, Thomas Trappenberg
2014	C	`conf`	Visualizing Hierarchical Representation in a Multilayered Restricted RBF Network. ICANN Pitoyo Hartono, Paul Hollensen, Thomas Trappenberg
2013	B	`conf`	Biologically plausible feature selection through relative correlation. IJCNN Patrick C. Connor, Thomas Trappenberg
2013	B	`conf`	Bubbles in the robot. IJCNN Thomas Trappenberg
2013	B	`conf`	Classificability-regulated self-organizing map using restricted RBF. IJCNN Pitoyo Hartono, Thomas Trappenberg
2013	J	`jnl`	Improved Path Integration Using a Modified Weight Combination Method. Cogn. Comput. Warren A. Connors, Thomas Trappenberg
2012	—	`conf`	Internal representation of sensory information for training autonomous robot. SCIS&ISIS Pitoyo Hartono, Thomas Trappenberg
2012	J	`jnl`	Spatial Interactions in the Superior Colliculus Predict Saccade Behavior in a Neural Field Model. J. Cogn. Neurosci. Robert A. Marino, Thomas Trappenberg, Michael Dorris, Douglas P. Munoz
2011	J	`jnl`	A Characterization of the Combined Effects of Overlap and Imbalance on the SVM Classifier CoRR Misha Denil, Thomas Trappenberg
2011	—	`conf`	Characterizing a Brain-Based Value-Function Approximator. Canadian AI Patrick C. Connor, Thomas Trappenberg
2011	—	`conf`	Comparison of Learned versus Engineered Features for Classification of Mine Like Objects from Raw Sonar Images. Canadian AI Paul Hollensen, Warren A. Connors, Thomas Trappenberg
2011	B	`conf`	Internal topographical structure in training autonomous robot. SMC Pitoyo Hartono, Thomas Trappenberg
2010	—	`conf`	Detection of Mine-Like Objects Using Restricted Boltzmann Machines. Canadian AI Warren A. Connors, Patrick C. Connor, Thomas Trappenberg
2010	—	`conf`	Overlap versus Imbalance. Canadian AI Misha Denil, Thomas Trappenberg
2010	B	`conf`	Selective attention improves self-organization of cortical maps with multiple inputs. IJCNN Thomas Trappenberg, Aya Saito, Pitoyo Hartono
2009	—	`book`	Fundamentals of Computational Neuroscience (2. ed.). Thomas Trappenberg
2009	B	`conf`	Learning Intialized by Topologically Correct Representation. SMC Pitoyo Hartono, Thomas Trappenberg
2009	—	`conf`	Top-Down Control of Learning in Biological Self-Organizing Maps. WSOM Thomas Trappenberg, Pitoyo Hartono, Douglas Rasmusson
2008	J	`jnl`	Modeling the integration of expectations in visual search with centre-surround neural fields. Neural Networks Joshua P. Salmon, Thomas Trappenberg
2007	J	`jnl`	Computational consequences of experimentally derived spike-time and weight dependent plasticity rules. Biol. Cybern. Dominic I. Standage, Sajiya Jalil, Thomas Trappenberg
2007	B	`conf`	The Trouble with Weight-Dependent STDP. IJCNN Dominic I. Standage, Thomas Trappenberg
2006	B	`conf`	A Heuristic for Free Parameter Optimization with Support Vector Machines. IJCNN Matthew Boardman, Thomas Trappenberg
2006	J	`jnl`	Input Variable Selection: Mutual Information and Linear Mixing Measures. IEEE Trans. Knowl. Data Eng. Thomas Trappenberg, Jie Ouyang, Andrew D. Back
2006	J	`jnl`	Rapid learning and robust recall of long sequences in modular associator networks. Neurocomputing Michael Lawrence, Thomas Trappenberg, Alan Fine
2005	B	`conf`	A continuous attractor neural network model of divided visual attention. IJCNN Dominic I. Standage, Thomas Trappenberg, Raymond M. Klein
2005	B	`conf`	A multi-modular associator network for simple temporal sequence learning and generation. ESANN Michael Lawrence, Thomas Trappenberg, Alan Fine
2005	B	`conf`	Coverage-performance estimation for classification with ambiguous data. ESANN Thomas Trappenberg
2005	B	`conf`	Differences in the subthreshold dynamics of leaky integrate-and-fire and Hodgkin-Huxley neuron models. IJCNN Dominic I. Standage, Thomas Trappenberg
2005	J	`jnl`	Modelling divided visual attention with a winner-take-all network. Neural Networks Dominic I. Standage, Thomas Trappenberg, Raymond M. Klein
2005	B	`conf`	Motivational modulation of endogenous inputs to the superior colliculus. IJCNN Jason Satel, Thomas Trappenberg, Raymond M. Klein
2005	J	`jnl`	Multi-packet regions in stabilized continuous attractor networks. Neurocomputing Thomas Trappenberg, Dominic I. Standage
2004	J	`jnl`	Self-organising continuous attractor networks with multiple activity packets, and the representation of space. Neural Networks Simon M. Stringer, Edmund T. Rolls, Thomas Trappenberg
2003	J	`jnl`	Self-organizing continuous attractor networks and motor function. Neural Networks Simon M. Stringer, Edmund T. Rolls, Thomas Trappenberg, Ivan E. Tavares de Araújo
2001	—	`conf`	Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes. NIPS Thomas Trappenberg, Edmund T. Rolls, Simon M. Stringer
2001	J	`jnl`	Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Trans. Neural Networks Andrew D. Back, Thomas Trappenberg
2000	—	`conf`	A Classification Scheme for Applications with Ambiguous Data. IJCNN (6) Thomas Trappenberg, Andrew D. Back
1999	B	`conf`	Input variable selection using independent component analysis. IJCNN Andrew D. Back, Thomas Trappenberg
1999	B	`conf`	Modeling time-varying processes by unfolding the time domain. IJCNN Lars Kindermann, Thomas Trappenberg
1998	B	`conf`	Dynamic Cooperation and Competition in a Network of Spiking Neurons. ICONIP Thomas Trappenberg
1997	—	`conf`	Neural field model of oculomotor preparation and disengagement. ICNN Thomas Trappenberg, S. Simpson, Raymond M. Klein, P. McMullen, Douglas P. Munoz, Michael Dorris
1997	—	`conf`	Non-monotone network dynamics; preliminary results. ICNN Thomas Trappenberg
1994	J	`jnl`	High Speed Monte Carlo Simulations on Vector Parallel Computers. Parallel Algorithms Appl. K. J. M. Moriarty, Sergiu Sanielevici, Thomas Trappenberg