| 2025 | ICMLA | Causal Autoencoder-like Generation of Feedback Fuzzy Cognitive Maps with an LLM Agent. | Akash Kumar Panda, Olaoluwa Adigun, Bart Kosko |
| 2024 | ICMLA | Training Deep Neural Classifiers with Soft Diamond Regularizers. | Olaoluwa Adigun, Bart Kosko |
| 2024 | IJCNN | Bidirectional Variational Autoencoders. | Bart Kosko, Olaoluwa Adigun |
| 2023 | ICMLA | Bidirectional Backpropagation Autoencoding Networks for Image Compression and Denoising. | Olaoluwa Adigun, Bart Kosko |
| 2023 | SMC | Hidden Priors for Bayesian Bidirectional Backpropagation. | Olaoluwa Adigun, Bart Kosko |
| 2022 | ICMLA | Deeper Bidirectional Neural Networks with Generalized Non-Vanishing Hidden Neurons. | Olaoluwa Adigun, Bart Kosko |
| 2022 | ICMLA | Bayesian Rule Ontologies For XAI Classification and Regression. | Akash Kumar Panda, Bart Kosko |
| 2021 | ICMLA | Bidirectional Backpropagation for High-Capacity Blocking Networks. | Olaoluwa Adigun, Bart Kosko |
| 2021 | ICMLA | Deeper Neural Networks with Non-Vanishing Logistic Hidden Units: NoVa vs. ReLU Neurons. | Olaoluwa Adigun, Bart Kosko |
| 2021 | IJCNN | Bayesian Bidirectional Backpropagation Learning. | Olaoluwa Adigun, Bart Kosko |
| 2020 | IJCNN | High Capacity Neural Block Classifiers with Logistic Neurons and Random Coding. | Olaoluwa Adigun, Bart Kosko |
| 2018 | ICMLA | Training Generative Adversarial Networks with Bidirectional Backpropagation. | Olaoluwa Adigun, Bart Kosko |
| 2017 | IJCNN | Using noise to speed up video classification with recurrent backpropagation. | Olaoluwa Adigun, Bart Kosko |
| 2017 | IJCNN | Generalized mixture representations and combinations for additive fuzzy systems. | Bart Kosko |
| 2013 | IJCNN | Noise benefits in backpropagation and deep bidirectional pre-training. | Kartik Audhkhasi, Osonde Osoba, Bart Kosko |
| 2013 | IJCNN | Noisy hidden Markov models for speech recognition. | Kartik Audhkhasi, Osonde Osoba, Bart Kosko |
| 2011 | IJCNN | Triply fuzzy function approximation for Bayesian inference. | Osonde Osoba, Sanya Mitaim, Bart Kosko |
| 2011 | IJCNN | Noise benefits in the expectation-maximization algorithm: Nem theorems and models. | Osonde Osoba, Sanya Mitaim, Bart Kosko |
| 2009 | ICASSP | Quantizer noise benefits in nonlinear signal detection with alpha-stable channel noise. | Ashok Patel, Bart Kosko |
| 2009 | IJCNN | Adaptive fuzzy priors for Bayesian inference. | Osonde Osoba, Sanya Mitaim, Bart Kosko |
| 2009 | IJCNN | Neural signal-detection noise benefits based on error probability. | Ashok Patel, Bart Kosko |
| 2008 | ICASSP | Optimal noise benefits in Neyman-Pearson signal detection. | Ashok Patel, Bart Kosko |
| 2007 | ICASSP | Levy Noise Benefits in Neural Signal Detection. | Ashok Patel, Bart Kosko |
| 2006 | IJCNN | Mutual-Information Noise Benefits in Brownian Models of Continuous and Spiking Neurons. | Ashok Patel, Bart Kosko |
| 2005 | IJCNN | Noise benefits in spiking retinal and sensory neuron models. | Ashok Patel, Bart Kosko |
| 2003 | IJCNN | Almost all noise types can improve the mutual information of threshold neurons that detect subthreshold signals. | Bart Kosko, Sanya Mitaim |
| 1998 | ICML | Stochastic Resonance with Adaptive Fuzzy Systems. | Sanya Mitaim, Bart Kosko |
| 1998 | SMC | Neural fuzzy stochastic resonance. | Sanya Mitaim, Bart Kosko |
| 1993 | VR | Virtual Worlds as Fuzzy Cognitive Maps. | Julie A. Dickerson, Bart Kosko |
| 1992 | ICASSP | Fuzzy subimage classification in image sequence coding. | Seong-Gon Kong, Bart Kosko |
| 1990 | IJCNN | Comparison of fuzzy and neural truck backer-upper control systems. | Seong-Gon Kong, Bart Kosko |
| 1990 | IJCNN | Stochastic competitive learning. | Bart Kosko |