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ORCIDAnthony S. Maida
Anthony Maida
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- affiliation: University of Louisiana at Lafayette, LA, USA
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2020 – today
- 2024
[j29]Nazmul Shahadat, Anthony S. Maida:
Cross channel weight sharing for image classification. Image Vis. Comput. 141: 104872 (2024)- [j28]Sai Venkatesh Chilukoti
, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei:
A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric. BMC Medical Informatics Decis. Mak. 24(1): 37 (2024) - [c41]Nazmul Shahadat, Anthony S. Maida:
Improving Axial-Attention Network via Cross-Channel Weight Sharing. FLAIRS 2024 - [c40]Nazmul Shahadat, Anthony S. Maida:
Deep Residual 1-Dimensional Convolutional Neural Networks in Vision. ICPR (22) 2024: 129-144 - [i24]Ali Mohammadjafari, Anthony S. Maida, Raju Gottumukkala:
From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems. CoRR abs/2410.01066 (2024) - 2023
- [j27]Matin Hosseini, Anthony Maida, Seyedmajid Hosseini, Raju Gottumukkala:
Inception Recurrent Neural Network Architecture for Video Frame Prediction. SN Comput. Sci. 4(1): 69 (2023) - [c39]Nazmul Shahadat, Anthony S. Maida:
Deep Separable Hypercomplex Networks. FLAIRS 2023 - [i23]Nazmul Shahadat, Anthony S. Maida:
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication. CoRR abs/2301.04623 (2023) - [i22]Nazmul Shahadat, Anthony S. Maida:
Deep Axial Hypercomplex Networks. CoRR abs/2301.04626 (2023) - [i21]Nazmul Shahadat, Anthony S. Maida:
Deep Residual Axial Networks. CoRR abs/2301.04631 (2023) - [i20]Nelly Elsayed, Zag ElSayed, Anthony S. Maida:
LiteLSTM Architecture Based on Weights Sharing for Recurrent Neural Networks. CoRR abs/2301.04794 (2023) - [i19]Majid Hosseini, Morteza Bodaghi, Ravi Teja Bhupatiraju, Anthony Maida, Raju Gottumukkala:
Multimodal Stress Detection Using Facial Landmarks and Biometric Signals. CoRR abs/2311.03606 (2023) - 2022
- [j26]Anthony Triche, Anthony S. Maida, Ashok Kumar:
Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks. Neural Networks 151: 16-33 (2022) - [c38]Nelly Elsayed, Zag ElSayed, Anthony S. Maida:
LiteLSTM Architecture for Deep Recurrent Neural Networks. ISCAS 2022: 1304-1308 - [i18]Nelly Elsayed, Zag ElSayed, Anthony S. Maida:
LiteLSTM Architecture for Deep Recurrent Neural Networks. CoRR abs/2201.11624 (2022) - [i17]Nelly Elsayed, Zag ElSayed, Anthony S. Maida:
Vision-Based American Sign Language Classification Approach via Deep Learning. CoRR abs/2204.04235 (2022) - 2021
- [j25]Md Fazle Rabby, Yazhou Tu, Md. Imran Hossen, Insup Lee, Anthony S. Maida, Xiali Hei:
Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction. BMC Medical Informatics Decis. Mak. 21(1): 101 (2021) - [c37]Andrew Wise, Anthony S. Maida, Ashok Kumar:
Attention Augmented CNNs for Musical Instrument Identification. EUSIPCO 2021: 376-380 - [c36]Chase J. Gaudet, Anthony S. Maida:
Removing Dimensional Restrictions On Complex/Hyper-Complex Neural Networks. ICIP 2021: 319-323 - [i16]Md Fazle Rabby, Yazhou Tu, Md. Imran Hossen, Insup Lee, Anthony S. Maida, Xiali Hei:
Stacked LSTM Based Deep Recurrent Neural Network with Kalman Smoothing for Blood Glucose Prediction. CoRR abs/2101.06850 (2021) - [i15]Nazmul Shahadat, Anthony S. Maida:
Adding Quaternion Representations to Attention Networks for Classification. CoRR abs/2110.01185 (2021) - 2020
- [j24]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Reduced-gate convolutional long short-term memory using predictive coding for spatiotemporal prediction. Comput. Intell. 36(3): 910-939 (2020) - [c35]Matin Hosseini, Anthony S. Maida, Majid Hosseini, Raju Gottumukkala:
Inception LSTM for Next-frame Video Prediction (Student Abstract). AAAI 2020: 13809-13810 - [i14]Matin Hosseini, Anthony S. Maida:
Hierarchical Predictive Coding Models in a Deep-Learning Framework. CoRR abs/2005.03230 (2020) - [i13]Chase J. Gaudet, Anthony S. Maida:
Generalizing Complex/Hyper-complex Convolutions to Vector Map Convolutions. CoRR abs/2009.04083 (2020)
2010 – 2019
- 2019
- [j23]Siva R. Venna, Amirhossein Tavanaei, Raju N. Gottumukkala, Vijay V. Raghavan, Anthony S. Maida, Stephen Nichols:
A Novel Data-Driven Model for Real-Time Influenza Forecasting. IEEE Access 7: 7691-7701 (2019) - [j22]Amirhossein Tavanaei, Anthony Maida:
BP-STDP: Approximating backpropagation using spike timing dependent plasticity. Neurocomputing 330: 39-47 (2019) - [j21]Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothée Masquelier, Anthony Maida:
Deep learning in spiking neural networks. Neural Networks 111: 47-63 (2019) - [c34]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
An Analysis of Univariate and Multivariate Electrocardiography Signal Classification. ICMLA 2019: 396-399 - [c33]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Reduced-Gate Convolutional LSTM Architecture for Next-Frame Video Prediction Using Predictive Coding. IJCNN 2019: 1-9 - [c32]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Gated Recurrent Neural Networks Empirical Utilization for Time Series Classification. iThings/GreenCom/CPSCom/SmartData 2019: 1207-1210 - [i12]Matin Hosseini, Anthony S. Maida, Majid Hosseini, Raju N. Gottumukkala:
Inception-inspired LSTM for Next-frame Video Prediction. CoRR abs/1909.05622 (2019) - 2018
- [j20]Amirhossein Tavanaei, Timothée Masquelier, Anthony S. Maida:
Representation learning using event-based STDP. Neural Networks 105: 294-303 (2018) - [j19]Amirhossein Tavanaei, Anthony S. Maida:
Training a Hidden Markov Model with a Bayesian Spiking Neural Network. J. Signal Process. Syst. 90(2): 211-220 (2018) - [c31]Ege Beyazit, Matin Hosseini, Anthony Maida, Xindong Wu:
Learning Simplified Decision Boundaries from Trapezoidal Data Streams. ICANN (1) 2018: 508-517 - [c30]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Empirical Activation Function Effects on Unsupervised Convolutional LSTM Learning. ICTAI 2018: 336-343 - [c29]Chase J. Gaudet, Anthony S. Maida:
Deep Quaternion Networks. IJCNN 2018: 1-8 - [c28]Amirhossein Tavanaei, Raju Gottumukkala, Anthony S. Maida, Vijay V. Raghavan:
Unsupervised Learning to Rank Aggregation using Parameterized Function Optimization. IJCNN 2018: 1-8 - [c27]Amirhossein Tavanaei, Zachary Kirby, Anthony S. Maida:
Training Spiking ConvNets by STDP and Gradient Descent. IJCNN 2018: 1-8 - [i11]Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothée Masquelier, Anthony S. Maida:
Deep Learning in Spiking Neural Networks. CoRR abs/1804.08150 (2018) - [i10]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Reduced-Gate Convolutional LSTM Using Predictive Coding for Spatiotemporal Prediction. CoRR abs/1810.07251 (2018) - [i9]Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification. CoRR abs/1812.07683 (2018) - 2017
- [j18]Amirhossein Tavanaei, Anthony S. Maida:
A spiking network that learns to extract spike signatures from speech signals. Neurocomputing 240: 191-199 (2017) - [c26]Amirhossein Tavanaei, Nishanth Anandanadarajah, Anthony S. Maida, Rasiah Loganantharaj:
A deep learning model for predicting tumor suppressor genes and oncogenes from PDB structure. BIBM 2017: 613-617 - [c25]Amirhossein Tavanaei, Anthony S. Maida:
Bio-inspired Multi-layer Spiking Neural Network Extracts Discriminative Features from Speech Signals. ICONIP (6) 2017: 899-908 - [c24]Amirhossein Tavanaei, Anthony S. Maida:
Multi-layer unsupervised learning in a spiking convolutional neural network. IJCNN 2017: 2023-2030 - [i8]Amirhossein Tavanaei, Anthony S. Maida:
Bio-Inspired Multi-Layer Spiking Neural Network Extracts Discriminative Features from Speech Signals. CoRR abs/1706.03170 (2017) - [i7]Amirhossein Tavanaei, Timothée Masquelier, Anthony S. Maida:
Representation Learning using Event-based STDP. CoRR abs/1706.06699 (2017) - [i6]Amirhossein Tavanaei, Anthony S. Maida:
BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity. CoRR abs/1711.04214 (2017) - [i5]Chase J. Gaudet, Anthony S. Maida:
Deep Quaternion Networks. CoRR abs/1712.04604 (2017) - 2016
- [c23]Amirhossein Tavanaei, Anthony S. Maida, Arun Kaniymattam, Rasiah Loganantharaj:
Towards recognition of protein function based on its structure using deep convolutional networks. BIBM 2016: 145-149 - [c22]Padraic D. Edgington, Anthony S. Maida:
Exact Particle Filter Modularization Improves Runtime Performance. ECAI 2016: 1397-1405 - [c21]Amirhossein Tavanaei, Timothée Masquelier, Anthony S. Maida:
Acquisition of visual features through probabilistic spike-timing-dependent plasticity. IJCNN 2016: 307-314 - [i4]Amirhossein Tavanaei, Anthony S. Maida:
A Spiking Network that Learns to Extract Spike Signatures from Speech Signals. CoRR abs/1606.00802 (2016) - [i3]Amirhossein Tavanaei, Anthony S. Maida:
Training a Hidden Markov Model with a Bayesian Spiking Neural Network. CoRR abs/1606.00825 (2016) - [i2]Amirhossein Tavanaei, Timothée Masquelier, Anthony S. Maida:
Acquisition of Visual Features Through Probabilistic Spike-Timing-Dependent Plasticity. CoRR abs/1606.01102 (2016) - [i1]Amirhossein Tavanaei, Anthony S. Maida:
Bio-Inspired Spiking Convolutional Neural Network using Layer-wise Sparse Coding and STDP Learning. CoRR abs/1611.03000 (2016) - 2015
- [c20]Amirhossein Tavanaei, Anthony S. Maida:
Studying the interaction of a hidden Markov model with a Bayesian spiking neural network. MLSP 2015: 1-6 - 2013
- [c19]Ashish Gupta, Murat Ayhan, Anthony Maida:
Natural Image Bases to Represent Neuroimaging Data. ICML (3) 2013: 987-994 - [c18]Blake Lemoine, Anthony S. Maida:
GPU facilitated unsupervised visual feature acquisition in spiking neural networks. IJCNN 2013: 1-6 - [c17]John P. McCaffery, Anthony S. Maida:
Toward a causal topic model for video scene analysis. IJCNN 2013: 1-8 - 2011
- [j17]Naresh N. Vempala, Anthony S. Maida:
Effects of memory size on melody recognition in a simulation of cohort theory. Cogn. Syst. Res. 12(1): 66-78 (2011)
2000 – 2009
- 2009
- [c16]Derek James, Anthony S. Maida:
Sequential hierarchical recruitment learning in a network of spiking neurons. IJCNN 2009: 1407-1413 - [c15]Steele A. Russell, Anthony S. Maida:
Performance of generalized multi-layered perceptrons and layered arbitrarily connected networks trained using the Levenberg-Marquardt method. IJCNN 2009: 2725-2731 - [c14]Jan-Phillip Tiesel, Anthony S. Maida:
Using parallel GPU architecture for simulation of planar I/F networks. IJCNN 2009: 3118-3123 - [c13]Naresh N. Vempala, Anthony S. Maida:
Modeling melody recognition using a sequence recognition neural network with meta-level processes. IJCNN 2009: 3204-3211 - 2007
- [j16]Ahmed A. Moustafa, Anthony S. Maida:
Using TD learning to simulate working memory performance in a model of the prefrontal cortex and basal ganglia. Cogn. Syst. Res. 8(4): 262-281 (2007) - 2006
- [j15]Cengiz Günay, Anthony S. Maida:
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks. Biol. Cybern. 94(1): 33-45 (2006) - [j14]Benjamin A. Rowland, Anthony S. Maida, Istvan S. N. Berkeley:
Synaptic noise as a means of implementing weight-perturbation learning. Connect. Sci. 18(1): 69-79 (2006) - [j13]Cengiz Günay, Anthony S. Maida:
Using temporal binding for hierarchical recruitment of conjunctive concepts over delayed lines. Neurocomputing 69(4-6): 317-367 (2006) - [j12]Arun Lakhotia, Suresh Golconda, Anthony Maida, Pablo Mejia, Amit Puntambeker, Guna Seetharaman, Scott Wilson:
CajunBot: Architecture and algorithms. J. Field Robotics 23(8): 555-578 (2006) - 2004
- [c12]Benjamin A. Rowland, Anthony S. Maida:
Spatiotemporal Novelty Detection Using Resonance Networks. FLAIRS 2004: 676-681 - 2003
- [j11]Cengiz Günay, Anthony S. Maida:
Temporal binding as an inducer for connectionist recruitment learning over delayed lines. Neural Networks 16(5-6): 593-600 (2003) - [c11]Cengiz Günay, Anthony S. Maida:
Using temporal binding for connectionist recruitment learning over delayed lines. IJCNN 2003: 224-229 - 2001
- [c10]Anthony S. Maida, Benjamin A. Rowland, Cengiz Günay:
Synchronized Firing in a Time-Delayed Neural Network. FLAIRS 2001: 485-488 - 2000
- [c9]Anthony S. Maida:
Identifying causal structure in a biological neural network. ICTAI 2000: 126-
1990 – 1999
- 1999
- [c8]Michail G. Lagoudakis, Anthony S. Maida:
Robot Navigation with a Polar Neural Map. AAAI/IAAI 1999: 965 - [c7]Michail G. Lagoudakis, Anthony S. Maida:
Neural maps for mobile robot navigation. IJCNN 1999: 2011-2016 - 1997
- [j10]Anthony S. Maida, Shaohua Tang:
Description-based communication for autonomous agents under ideal conditions. J. Exp. Theor. Artif. Intell. 9(1): 103-135 (1997) - 1995
- [j9]Valerie L. Shalin, Wray L. Buntine, S. Gillian Parker, James Higginbotham, Afzal Ballim, Anthony S. Maida, Charles R. Fletcher, David L. Kemerer, Lawrence A. Shapiro, Richard Wyatt, Deepak Kumar, Selmer Bringsjord, Bill Patterson:
Book reviews. Minds Mach. 5(2): 257-307 (1995) - 1993
- [j8]Anthony S. Maida:
Propositionally representing incomplete knowledge about existence. J. Exp. Theor. Artif. Intell. 5(2-3): 185-197 (1993) - [j7]Minkoo Kim, Anthony S. Maida:
Reliability Measure Theory: A Nonmonotonic Semantics. IEEE Trans. Knowl. Data Eng. 5(1): 41-51 (1993) - 1992
- [c6]Anthony S. Maida:
Knowledge Representation Requirements for Description-Based Communication. KR 1992: 232-243 - 1991
- [j6]Anthony S. Maida:
Maintaining Mental Models of Agents who have Existential Misconceptions. Artif. Intell. 50(3): 331-383 (1991) - [j5]Anthony S. Maida, Jacques Wainer, Sehyeong Cho:
A syntactic approach to introspection and reasoning about the beliefs of other agents. Fundam. Informaticae 15(3-4): 333-356 (1991)
1980 – 1989
- 1989
- [j4]Kenzo Iwama, Anthony S. Maida:
Organizing and integrating edge segments for texture discrimination. J. Exp. Theor. Artif. Intell. 1(2): 113-132 (1989) - 1987
- [c5]Minkoo Kim, Anthony S. Maida:
Frame systems and inheritance systems. FJCC 1987: 636-643 - [c4]Anthony S. Maida:
A Uniform Architecture for Rule-based Meta Reasoning and Representation. ISMIS 1987: 115-122 - [c3]Minkoo Kim, Anthony S. Maida:
Frame and Inheritance Systems. ISMIS 1987: 209-216 - 1985
- [j3]Anthony S. Maida:
Selecting a Humanly Understandable Knowledge Representation for Reasoning About Knowledge. Int. J. Man Mach. Stud. 22(2): 151-161 (1985) - 1984
- [c2]Anthony S. Maida:
Processing Entailments and Accessing Facts in a Uniform Frame System. AAAI 1984: 233-236 - 1983
- [j2]Anthony S. Maida:
Review of "Machine Intelligence and Related Topics: An Information Scientist's Weekend Book by Donald Michie"; Gordon & Breach, Science Publishers, Inc., ISBN 0-677-05560-9, 1982. SIGART Newsl. 85: 27-28 (1983) - [c1]Anthony S. Maida:
Knowing Intensional Individuals, and Reasoning About Knowing Intensional Individuals. IJCAI 1983: 382-384 - 1982
- [j1]Anthony S. Maida, Stuart C. Shapiro:
Intensional Concepts in Propositional Semantic Networks. Cogn. Sci. 6(4): 291-330 (1982)
Coauthor Index
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