Anthony S. Maida
Associate Professor of Computer Science
Biological Artificial Intelligence Lab

School of Computing and Informatics,
University of Louisiana at Lafayette,
Room 355 James R. Oliver Hall,
Lafayette, Louisiana 70504-3694,
USA

Telephone: (337) 482-6308
E-mail: maida@louisiana.edu
Google Scholar



Current and Recent Projects

Quaternion weight-sharing Context in predictive coding Spiking, postsynaptic currents, and STDP learning
in axial attention

Selected Publications

  • Removing Dimensional Restrictions on Complex/Hyper-Complex Neural Networks
    Chase Gaudet, Anthony S. Maida
    IEEE International Conference on Image Processing, Sept 19-22, Anchorage, 2021, to appear.

  • Stacked LSTM Based Deep Recurrent Neural Network with Kalman Smoothing for Blood Glucose Prediction
    Md F. Rabby, Y. Tu, Md I. Hossen, I. Lee, A. Maida, X. Hei
    BMC Medical Informatics and Decision Making, 21:101, 2021, doi: 10.1186/s12911-021-01462-5.

  • Direct Normal Irradiance Forecasting using Multivariate Recurrent Networks
    M. Hosseini, S. Katragadda, J. Wojtkiewicz, R. Gottumukkala, A. S. Maida, T. L. Chambers
    Energies, 13(15), 2020, 1394, Access here.

  • Reduced-Gate Convolutional Long Short-Term Memory using Predictive Coding for Spatiotemporal Prediction
    N. Elsayed, A. S. Maida, M. Bayoumi
    Computational Intelligence, 36, 2020, 910-939.

  • Deep Learning in Spiking Neural Networks
    A. Tavanaei, M. Ghodrati, S. R. Kheradpisheh, T. Masquelier, A. S. Maida
    Neural Networks, 111, 2019, 47-63.

  • Deep Quaternion Networks
    Chase Gaudet, Anthony S. Maida
    International Joint Conference on Neural Networks (IJCNN), July 8-13, Rio de Janeiro, 2018, 1565-1572.

  • BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity
    Amirhossein Tavanaei, Anthony S. Maida
    Neuralcomputing, 330, 2018, 39-47.

  • Representation Learning using Event-based STDP
    Amirhossein Tavanaei, Timothée Masquelier, Anthony S. Maida
    Neural Networks, 105, 2018, 294-303.

  • Training a Hidden Markov Model with a Bayesian Spiking Neural Network
    Amirhossein Tavanaei, Anthony S. Maida
    Journal of Signal Processing Systems, Springer, 90(2), 2018, 211-220.

  • Multi-Layer Unsupervised Learning in a Convolutional Neural Network
    Amirhossein Tavanaei, Anthony S. Maida
    International Joint Conference on Neural Networks (IJCNN), Anchorage, May 2017, 2023-2030.

  • A Spiking Network that Learns to Extract Spike Signatures from Speech Signals
    Amirhossein Tavanaei, Anthony S. Maida
    Neurocomputing, 2017, 240, 191-199.

  • Acquisition of Visual Features through Probabilistic Spike-Timing-Dependent Plasticity,
    A. Tavanaei, T. Masquelier, A. Maida
    International Joint Conference on Neural Networks (IJCNN), Vancouver, July 2016, 307-314.

  • Cognitive Computing and Neural Networks: Reverse Engineering the Brain
    Anthony S. Maida
    Handbook of Statistics: Vol 35, Cognitive Computing,, Elsevier, 2016, 39-78.
    V. N. Gudivada, V. Raghavan, V. Govindaraju, C. R. Rao (Eds).

  • Exact Particle Filter Modularization Improves Runtime Performance
    Padraic Edgington, Anthony S. Maida
    22nd European Conference on Artificial Intelligence, The Hague, Holland, Aug 29 - Sept 2, 2016.

  • Training a Hidden Markov Model with a Bayesian Spiking Network
    Amirhossein Tavanaei, Anthony S. Maida
    Journal of Signal Processing Systems, 2016, 1-10, DOI:10.1007/s11265-016-1153-2.

  • Natural Image Bases to Represent Neuroimaging Data
    A. Gupta, M. Ayhan, A. S. Maida
    Journal of Machine Learning Research, 2013, 28(3), 987-994.

  • GPU Facilitated Unsupervised Visual Feature Acquisition in Spiking Neural Networks
    Blake Lemoine and Anthony S. Maida
    The 2013 International Joint Conference on Neural Networks, Dallas, Texas, August 4-9, 2013, 1840-1845.

  • Toward a Causal Topic Model for Visual Scene Analysis
    John P. McCaffery and Anthony S. Maida
    The 2013 International Joint Conference on Neural Networks, Dallas, Texas, August 4-9, 2013, 1674-1681.

  • Natural Image Bases to Represent Neuroimaging Data
    Ashish Gupta, Murat Ayhan, and Anthony Maida
    Journal of Machine Learning Research: Workshop and Conference Proceedings, 2013, 28(3), 987-984.
    Accessible online here.

  • Effects of Memory Size on Melody Recognition in a Simulation of Cohort Theory
    Naresh N. Vempala and Anthony S. Maida
    Cognitive Systems Research, 2011, 12(1), 66-78.

    Accessible online here.

  • Modeling Melody Recognition Using a Cohort Network
    Naresh N. Vempala and Anthony S. Maida
    7th Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM), Jyvaskyla, Finland, August 12-16, 2009.
    Accessible online here.

  • Modeling Melody Recognition Using a Sequence Recognition Neural Network with Meta-Level Processes
    Naresh N. Vempala and Anthony S. Maida
    Proc Intl Joint Conf on Neural Networks (IJCNN), Atlanta, GA, June 14-19, 2009, 3204-3211.

  • Sequential Hierarchical Recruitment Learning in a Network of Spiking Neurons
    Derek James and Anthony S. Maida
    Proc Intl Joint Conf on Neural Networks (IJCNN), Atlanta, GA, June 14-19, 2009, 1407-1413.

  • Using Parallel GPU Architecture for Simulation of Planar I/F Networks
    Jan-Phillip Tiesel and Anthony S. Maida
    Proc Intl Joint Conf on Neural Networks (IJCNN), Atlanta, GA, June 14-19, 2009, 3118-3123.

  • Using TD Learning to Simulate Working Memory Performance in a Model of the Prefrontal Cortex and Basal Ganglia
    Ahmed Moustafa and Anthony S. Maida
    Cognitive Systems Research, 2007, 8, 262-281.
    Accessible online here.

  • Subgoal-based Local Navigation and Obstacle Avoidance Using a Grid-Distance Field
    A. Maida, S. Golconda, P. Mejia, A. Lakhotia, C. Cavanaugh
    International Journal of Vehicle Autonomous Systems (IJVAS), 2006, 4(2-4), 122-142.
    Preprint is here.

  • CajunBot: Architecture and Algorithms
    A. Lakhotia, S. Golconda, A. Maida, P. Mejia, A. Puntambeker, G. Seetharaman, S. Wilson
    Journal of Field Robotics, 2006, 23(8), 555-578.
    Accessible online here.

  • Synaptic Noise as a Means of Implementing Weight-perturbation Learning
    Benjamin A. Rowland, Anthony S. Maida, and Istvan S. N. Berkeley
    Connection Science, 2006, 18(1), 69-79.
    Accessible online here.

  • A Stochastic Population Approach to the Problem of Stable Recruitment Hierarchies in Spiking Neural Networks
    Cengiz Günay and Anthony S. Maida
    Biological Cybernetics, 2006, 94, 33-45.
    Accessible online here.

  • Using Temporal Binding for Hierarchical Recruitment of Conjunctive Concepts over Delayed Lines
    Cengiz Günay and Anthony S. Maida
    Neurocomputing, 2006, 69(4-6), 317-367.
    Accessible online here.

  • Spatiotemporal Novelty Detection Using Resonance Networks
    Benjamin Rowland and Anthony S. Maida
    Proceedings of the 17th Annual Florida AI Research Society Conference
    Miami Beach, FL, May 2004, pp. 676-681.

  • Temporal Binding as an Inducer for Connectionist Recruitment over Delayed Lines
    Cengiz Günay and Anthony S. Maida
    Neural Networks, 2003, 16(5-6), 593-600.
    Available here.

  • Using Temporal Binding for Connectionist Recruitment Learning over Delayed Lines
    Cengiz Günay and Anthony S. Maida
    Proceeding of the International Joint Conference on Neural Networks
    Portland, OR, July 2003, 224-229.

  • The Required Measures of Phase Segregation in Distributed Cortical Processing
    Cengiz Günay, Anthony S. Maida
    Proceeding of the International Joint Conference on Neural Networks
    Washington, DC, July 2001, 290-295.

  • Simulation of Planar I/F Networks with Delayed Connections
    Anthony S. Maida, Benjamin A. Rowland, and Cengiz Günay
    Proceeding of the International Joint Conference on Neural Networks
    Washington, DC, July 2001, 302-307.
    Available here.

  • Neural Maps for Mobile Robot Navigation
    Michail G. Lagoudakis and Anthony S. Maida
    Proceeding of the International Joint Conference on Neural Networks
    Washington, DC, July 1999.

  • Description-based Communication for Autonomous Agents under Ideal Conditions
    Anthony S. Maida and Shaohua Tang
    Journal of Experimental and Theoretical Artificial Intelligence, 1997, 9(1), 103-135.
    Available here.

  • Referent Misidentification and Recovery Among Communicating Agents
    Anthony S. Maida and Shaohua Tang
    Proceedings of the Second International Conference on Multiagent Systems
    Kyoto, Japan, December, 1996, AAAI press.

  • Reliability Measure Theory: A Nonmonotonic Semantics
    Minkoo Kim and Anthony S. Maida
    IEEE Transactions on Data and Knowledge Engineering, 1993, 5(1), 41-51.

  • Maintaining Mental Models of Agents who have Existential Misconceptions
    Anthony S. Maida
    Artificial Intelligence, 1991, 50(3), 331-383.

  • A Syntactic Approach to Introspection and Reasoning about the Beliefs of Other Agents
    Anthony S. Maida, Jacques Wainer, and Sehyeong Cho
    Fundamenta Informaticae, 1991, 15(3-4), 333-356.

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