Bart Kosko - RankMe

103 papers A* 1B 22C 8Misc 3Journal 54Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Agentic Leash: Extracting Causal Feedback Fuzzy Cognitive Maps with LLMs. CoRR Akash Kumar Panda, Olaoluwa Adigun, Bart Kosko
2025	J	`jnl`	Bidirectional Variational Autoencoders. CoRR Bart Kosko, Olaoluwa Adigun
2025	C	`conf`	Causal Autoencoder-like Generation of Feedback Fuzzy Cognitive Maps with an LLM Agent. ICMLA Akash Kumar Panda, Olaoluwa Adigun, Bart Kosko
2025	J	`jnl`	Causal Autoencoder-like Generation of Feedback Fuzzy Cognitive Maps with an LLM Agent. CoRR Akash Kumar Panda, Olaoluwa Adigun, Bart Kosko
2025	J	`jnl`	Controlled Causal Hallucinations Can Estimate Phantom Nodes in Multiexpert Mixtures of Fuzzy Cognitive Maps. CoRR Akash Kumar Panda, Bart Kosko
2024	B	`conf`	Bidirectional Variational Autoencoders. IJCNN Bart Kosko, Olaoluwa Adigun
2024	C	`conf`	Training Deep Neural Classifiers with Soft Diamond Regularizers. ICMLA Olaoluwa Adigun, Bart Kosko
2024	J	`jnl`	Training Deep Neural Classifiers with Soft Diamond Regularizers. CoRR Olaoluwa Adigun, Bart Kosko
2023	C	`conf`	Bidirectional Backpropagation Autoencoding Networks for Image Compression and Denoising. ICMLA Olaoluwa Adigun, Bart Kosko
2023	B	`conf`	Hidden Priors for Bayesian Bidirectional Backpropagation. SMC Olaoluwa Adigun, Bart Kosko
2023	J	`jnl`	Noise-boosted recurrent backpropagation. Neurocomputing Olaoluwa Adigun, Bart Kosko
2022	C	`conf`	Bayesian Rule Ontologies For XAI Classification and Regression. ICMLA Akash Kumar Panda, Bart Kosko
2022	C	`conf`	Deeper Bidirectional Neural Networks with Generalized Non-Vanishing Hidden Neurons. ICMLA Olaoluwa Adigun, Bart Kosko
2022	B	`conf`	Uniform Convergence of Probability Mixtures that Represent Combined Fuzzy Systems. FUZZ-IEEE Bart Kosko
2021	B	`conf`	Bayesian Bidirectional Backpropagation Learning. IJCNN Olaoluwa Adigun, Bart Kosko
2021	B	`conf`	Bayesian Pruned Random Rule Foams for XAI. FUZZ-IEEE Akash Kumar Panda, Bart Kosko
2021	J	`jnl`	Bidirectional Associative Memories: Unsupervised Hebbian Learning to Bidirectional Backpropagation. IEEE Trans. Syst. Man Cybern. Syst. Bart Kosko
2021	C	`conf`	Bidirectional Backpropagation for High-Capacity Blocking Networks. ICMLA Olaoluwa Adigun, Bart Kosko
2021	C	`conf`	Deeper Neural Networks with Non-Vanishing Logistic Hidden Units: NoVa vs. ReLU Neurons. ICMLA Olaoluwa Adigun, Bart Kosko
2021	J	`jnl`	Erratum to "Bidirectional Associative Memories: Unsupervised Hebbian Learning to Bidirectional Backpropagation". IEEE Trans. Syst. Man Cybern. Syst. Bart Kosko
2021	—	`conf`	Uniform Mixture Convergence of Continuously Transformed Fuzzy Systems. NAFIPS Bart Kosko
2020	J	`jnl`	Bidirectional Backpropagation. IEEE Trans. Syst. Man Cybern. Syst. Olaoluwa Adigun, Bart Kosko
2020	B	`conf`	Convergence of Generalized Probability Mixtures That Describe Adaptive Fuzzy Rule-based Systems. FUZZ-IEEE Bart Kosko
2020	B	`conf`	High Capacity Neural Block Classifiers with Logistic Neurons and Random Coding. IJCNN Olaoluwa Adigun, Bart Kosko
2020	J	`jnl`	Noise can speed backpropagation learning and deep bidirectional pretraining. Neural Networks Bart Kosko, Kartik Audhkhasi, Osonde Osoba
2020	—	`conf`	Random Fuzzy-Rule Foams for Explainable AI. NAFIPS Akash Kumar Panda, Bart Kosko
2019	J	`jnl`	Beyond DAGs: Modeling Causal Feedback with Fuzzy Cognitive Maps. CoRR Osonde Osoba, Bart Kosko
2019	J	`jnl`	Noise-boosted bidirectional backpropagation and adversarial learning. Neural Networks Olaoluwa Adigun, Bart Kosko
2018	J	`jnl`	Additive Fuzzy Systems: From Generalized Mixtures to Rule Continua. Int. J. Intell. Syst. Bart Kosko
2018	J	`jnl`	Noisy Expectation-Maximization: Applications and Generalizations. CoRR Osonde Osoba, Bart Kosko
2018	C	`conf`	Training Generative Adversarial Networks with Bidirectional Backpropagation. ICMLA Olaoluwa Adigun, Bart Kosko
2017	B	`conf`	Generalized mixture representations and combinations for additive fuzzy systems. IJCNN Bart Kosko
2017	B	`conf`	Using noise to speed up video classification with recurrent backpropagation. IJCNN Olaoluwa Adigun, Bart Kosko
2016	J	`jnl`	Noise-enhanced convolutional neural networks. Neural Networks Kartik Audhkhasi, Osonde Osoba, Bart Kosko
2015	—	`ch.`	Additive Fuzzy Systems as Generalized Probability Mixture Models. Fifty Years of Fuzzy Logic and its Applications Bart Kosko
2015	—	`conf`	Using Noise to Speed up Markov Chain Monte Carlo Estimation. INNS Conference on Big Data Brandon Franzke, Bart Kosko
2013	J	`jnl`	Corrigendum to "Noise enhanced clustering and competitive learning algorithms" [Neural Networks 37 (2013) 132-140]. Neural Networks Osonde Osoba, Bart Kosko
2013	B	`conf`	Noise benefits in backpropagation and deep bidirectional pre-training. IJCNN Kartik Audhkhasi, Osonde Osoba, Bart Kosko
2013	J	`jnl`	Noise-enhanced clustering and competitive learning algorithms. Neural Networks Osonde Osoba, Bart Kosko
2013	B	`conf`	Noisy hidden Markov models for speech recognition. IJCNN Kartik Audhkhasi, Osonde Osoba, Bart Kosko
2012	J	`jnl`	Triply fuzzy function approximation for hierarchical Bayesian inference. Fuzzy Optim. Decis. Mak. Osonde Osoba, Sanya Mitaim, Bart Kosko
2011	J	`jnl`	Bayesian Inference With Adaptive Fuzzy Priors and Likelihoods. IEEE Trans. Syst. Man Cybern. Part B Osonde Osoba, Sanya Mitaim, Bart Kosko
2011	J	`jnl`	Noise Benefits in Quantizer-Array Correlation Detection and Watermark Decoding. IEEE Trans. Signal Process. Ashok Patel, Bart Kosko
2011	B	`conf`	Noise benefits in the expectation-maximization algorithm: Nem theorems and models. IJCNN Osonde Osoba, Sanya Mitaim, Bart Kosko
2011	B	`conf`	Triply fuzzy function approximation for Bayesian inference. IJCNN Osonde Osoba, Sanya Mitaim, Bart Kosko
2010	J	`jnl`	Optimal Mean-Square Noise Benefits in Quantizer-Array Linear Estimation. IEEE Signal Process. Lett. Ashok Patel, Bart Kosko
2010	—	`conf`	Stochastic Resonance Noise Benefits in Markov Chain Monte Carlo Density Estimation. DMIN Brandon Franzke, Bart Kosko
2009	B	`conf`	Adaptive fuzzy priors for Bayesian inference. IJCNN Osonde Osoba, Sanya Mitaim, Bart Kosko
2009	J	`jnl`	Error-probability noise benefits in threshold neural signal detection. Neural Networks Ashok Patel, Bart Kosko
2009	B	`conf`	Neural signal-detection noise benefits based on error probability. IJCNN Ashok Patel, Bart Kosko
2009	J	`jnl`	Optimal noise benefits in Neyman-Pearson and inequality-constrained statistical signal detection. IEEE Trans. Signal Process. Ashok Patel, Bart Kosko
2009	Misc	`conf`	Quantizer noise benefits in nonlinear signal detection with alpha-stable channel noise. ICASSP Ashok Patel, Bart Kosko
2008	Misc	`conf`	Optimal noise benefits in Neyman-Pearson signal detection. ICASSP Ashok Patel, Bart Kosko
2008	J	`jnl`	Stochastic Resonance in Continuous and Spiking Neuron Models With Levy Noise. IEEE Trans. Neural Networks Ashok Patel, Bart Kosko
2007	—	`conf`	Levy Noise Benefits in Neural Signal Detection. ICASSP (3) Ashok Patel, Bart Kosko
2006	B	`conf`	Mutual-Information Noise Benefits in Brownian Models of Continuous and Spiking Neurons. IJCNN Ashok Patel, Bart Kosko
2005	J	`jnl`	Modeling gunshot bruises in soft body armor with an adaptive fuzzy system. IEEE Trans. Syst. Man Cybern. Part B Ian Lee, Bart Kosko, W. French Anderson
2005	B	`conf`	Noise benefits in spiking retinal and sensory neuron models. IJCNN Ashok Patel, Bart Kosko
2005	J	`jnl`	Stochastic resonance in noisy spiking retinal and sensory neuron models. Neural Networks Ashok Patel, Bart Kosko
2004	J	`jnl`	Adaptive stochastic resonance in noisy neurons based on mutual information. IEEE Trans. Neural Networks Sanya Mitaim, Bart Kosko
2004	J	`jnl`	Probable equivalence, superpower sets, and superconditionals. Int. J. Intell. Syst. Bart Kosko
2003	B	`conf`	Almost all noise types can improve the mutual information of threshold neurons that detect subthreshold signals. IJCNN Bart Kosko, Sanya Mitaim
2003	J	`jnl`	Stochastic resonance in noisy threshold neurons. Neural Networks Bart Kosko, Sanya Mitaim
2002	B	`conf`	A conditioning interval based on superconditionals and superpower sets. FUZZ-IEEE Bart Kosko
2001	J	`jnl`	The shape of fuzzy sets in adaptive function approximation. IEEE Trans. Fuzzy Syst. Sanya Mitaim, Bart Kosko
1998	J	`jnl`	Adaptive stochastic resonance. Proc. IEEE Sanya Mitaim, Bart Kosko
1998	J	`jnl`	Global stability of generalized additive fuzzy systems. IEEE Trans. Syst. Man Cybern. Part C Bart Kosko
1998	J	`jnl`	Neural Fuzzy Agents for Profile Learning and Adaptive Object Matching. Presence Teleoperators Virtual Environ. Sanya Mitaim, Bart Kosko
1998	B	`conf`	Neural fuzzy stochastic resonance. SMC Sanya Mitaim, Bart Kosko
1998	J	`jnl`	Special Issue On Intelligent Signal Processing. Proc. IEEE Simon Haykin, Bart Kosko
1998	A*	`conf`	Stochastic Resonance with Adaptive Fuzzy Systems. ICML Sanya Mitaim, Bart Kosko
1997	—	`conf`	Adaptive joint fuzzy sets for function approximation. ICNN Sanya Mitaim, Bart Kosko
1997	—	`conf`	Neural Fuzzy Agents for Database Search. CIA Sanya Mitaim, Bart Kosko
1997	—	`conf`	Neural Fuzzy Agents for Profile Learning and Object Matching. Agents Sanya Mitaim, Bart Kosko
1997	—	`conf`	Neural Fuzzy Agents that Learn a User's Preference Map. ADL Sanya Mitaim, Bart Kosko
1997	—	`conf`	Neural fuzzy agents that learn profiles and search databases. ICNN Sanya Mitaim, Bart Kosko
1997	J	`jnl`	Neural fuzzy motion estimation and compensation. IEEE Trans. Signal Process. Hyun Mun Kim, Bart Kosko
1996	J	`jnl`	Fuzzy function approximation with ellipsoidal rules. IEEE Trans. Syst. Man Cybern. Part B Julie A. Dickerson, Bart Kosko
1996	J	`jnl`	Fuzzy prediction and filtering in impulsive noise. Fuzzy Sets Syst. Hyun Mun Kim, Bart Kosko
1996	J	`jnl`	Fuzzy throttle and brake control for platoons of smart cars. Fuzzy Sets Syst. Hyun Mun Kim, Julie A. Dickerson, Bart Kosko
1995	J	`jnl`	Adaptive fuzzy frequency hopper. IEEE Trans. Commun. Peter J. Pacini, Bart Kosko
1995	J	`jnl`	Optimal fuzzy rules cover extrema. Int. J. Intell. Syst. Bart Kosko
1994	J	`jnl`	Fuzzy Systems as Universal Approximators. IEEE Trans. Computers Bart Kosko
1994	J	`jnl`	The probability monopoly. IEEE Trans. Fuzzy Syst. Bart Kosko
1994	J	`jnl`	Virtual Worlds as Fuzzy Cognitive Maps. Presence Teleoperators Virtual Environ. Julie A. Dickerson, Bart Kosko
1993	J	`jnl`	Addition as fuzzy mutual entropy. Inf. Sci. Bart Kosko
1993	—	`conf`	Fuzzy function learning with covariance ellipsoids. ICNN Julie A. Dickerson, Bart Kosko
1993	—	`conf`	Virtual Worlds as Fuzzy Cognitive Maps. VRAIS Julie A. Dickerson, Bart Kosko
1992	J	`jnl`	Adaptive fuzzy systems for backing up a truck-and-trailer. IEEE Trans. Neural Networks Seong-Gon Kong, Bart Kosko
1992	Misc	`conf`	Fuzzy subimage classification in image sequence coding. ICASSP Seong-Gon Kong, Bart Kosko
1992	—	`book`	Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. Bart Kosko
1991	J	`jnl`	Differential competitive learning for centroid estimation and phoneme recognition. IEEE Trans. Neural Networks Seong-Gon Kong, Bart Kosko
1991	J	`jnl`	Stochastic competitive learning. IEEE Trans. Neural Networks Bart Kosko
1990	B	`conf`	Comparison of fuzzy and neural truck backer-upper control systems. IJCNN Seong-Gon Kong, Bart Kosko
1990	B	`conf`	Stochastic competitive learning. IJCNN Bart Kosko
1990	J	`jnl`	Unsupervised learning in noise. IEEE Trans. Neural Networks Bart Kosko
1988	J	`jnl`	Bidirectional associative memories. IEEE Trans. Syst. Man Cybern. Bart Kosko
1988	—	`conf`	Feedback stability and unsupervised learning. ICNN Bart Kosko
1988	J	`jnl`	Hidden patterns in combined and adaptive knowledge networks. Int. J. Approx. Reason. Bart Kosko
1986	J	`jnl`	Counting with Fuzzy Sets. IEEE Trans. Pattern Anal. Mach. Intell. Bart Kosko
1986	J	`jnl`	Fuzzy Cognitive Maps. Int. J. Man Mach. Stud. Bart Kosko
1986	J	`jnl`	Fuzzy entropy and conditioning. Inf. Sci. Bart Kosko
1986	J	`jnl`	Fuzzy knowledge combination. Int. J. Intell. Syst. Bart Kosko