Integrating Induction & Instruction: Connectionist Advice Taking. - David C. Noelle; Garrison W. Cottrell (AAAI, 1994)

A Connectionist Model of Instructed Learning. - David C. Noelle (AAAI/IAAI, Vol. 2, 1996)

A Biologically Inspired Adaptive Working Memory for Robots. - Marjorie Skubic; David C. Noelle; D. Mitch Wilkes; Kazuhiko Kawamura; James M. Keller (AAAI Technical Report (5), 2004)

Neurocomputational Mechanisms for Generalization During the Sequential Learning of Multiple Tasks. - Ashish Gupta 005; David C. Noelle (IICAI, 2005)

A biologically inspired working memory framework for robots. - Joshua L. Phillips; David C. Noelle (RO-MAN, 2005)

Working memory and perception. - D. Mitchell Wilkes; Mert Tugcu; Jonathan E. Hunter; David C. Noelle (RO-MAN, 2005)

A Dual-Pathway Neural Network Model of Control Relinquishment in Motor Skill Learning. - Ashish Gupta 005; David C. Noelle (IJCAI, 2007)

Function Follows Form: Biologically Guided Functional Decomposition of Memory Systems. - David C. Noelle (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2008)

Preface. - Alexei V. Samsonovich; David C. Noelle; Shane T. Mueller (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2009)

On a Roadmap to Biologically Inspired Cognitive Agents. - Antonio Chella; Christian Lebiere; David C. Noelle; Alexei V. Samsonovich (BICA, 2011)

Interacting Complementary Learning Systems in Brains and Machines. - David C. Noelle (BICA, 2011)

Asymmetric Intercortical Projections Support The Learning Of Temporal Associations. - William Benjamin St. Clair; David C. Noelle (CogSci, 2011)

Generalisation benefits of output gating in a model of prefrontal cortex. - Trent Kriete; David C. Noelle (Connect. Sci., 2011)

A dual association model for the extinction of animal conditioning. - Ashish Gupta 005; Lovekesh Vig; David C. Noelle (Neurocomputing, 2011)

A Cognitive Model for Generalization during Sequential Learning. - Ashish Gupta 005; Lovekesh Vig; David C. Noelle (J. Robotics, 2011)

Implications of Polychronous Neuronal Groups for the Nature of Mental Representations. - William Benjamin St. Clair; David C. Noelle (CogSci, 2013)

Approximating the Value Function in the Actor Critic Architecture using the Temporal Dynamics of Spiking Neural Networks. - Jeffrey Rodny; David C. Noelle (CogSci, 2013)

Automatic formative assessment of exercises on knowledge representation in first-order logic. - Angelo Kyrilov; David C. Noelle (ITiCSE, 2013)

Robotic Learning Of The Delayed Saccade Task Using A Neurally Inspired Adaptive Working Memory System. - David C. Noelle; Justin Ray (CogSci, 2014)

Topological Dependence of Rate Code Stability. - William Benjamin St. Clair; David C. Noelle (CogSci, 2015)

A Case-Based Reasoning Approach to Providing High-Quality Feedback on Computer Programming Exercises. - Angelo Kyrilov; David C. Noelle (CogSci, 2015)

Lateral Inhibition Overcomes Limits of Temporal Difference Learning. - Jacob Rafati; David C. Noelle (CogSci, 2015)

Modeling the Role of Hippocampus in Extinction and Spontaneous Recovery. - Jeffrey Rodny; David C. Noelle (CogSci, 2015)

Neuronal Dynamics and Spatial Foraging. - Timothy M. Shea; Anne S. Warlaumont; Christopher T. Kello; David C. Noelle (CogSci, 2015)

Binary instant feedback on programming exercises can reduce student engagement and promote cheating. - Angelo Kyrilov; David C. Noelle (Koli Calling, 2015)

Using Automated Theorem Provers to Teach Knowledge Representation in First-Order Logic. - Angelo Kyrilov; David C. Noelle (CoRR, 2015)

Implications of polychronous neuronal groups for the continuity of mind. - William Benjamin St. Clair; David C. Noelle (Cogn. Process., 2015)

Toward a Simulation Platform for Comparing Computational Cognitive Neuroscience Models. - David C. Noelle (CogSci, 2016)

Do students need detailed feedback on programming exercises and can automated assessment systems provide it? - Angelo Kyrilov; David C. Noelle (J. Comput. Sci. Coll., 2016)

Indirection Explains Flexible Tuning of Neurons in Prefrontal Cortex. - David C. Noelle (CogSci, 2017)

A Conceptual Ladder from Spikes to Behavior: Toward the Neural Basis of Dynamic Choices at Multiple Scales. - Timothy M. Shea; David C. Noelle (CogSci, 2018)

Automated Plagiarism Detection for Computer Programming Exercises Based on Patterns of Resubmission. - Narjes Tahaei; David C. Noelle (ICER, 2018)

Unsupervised Methods For Subgoal Discovery During Intrinsic Motivation in Model-Free Hierarchical Reinforcement Learning. - Jacob Rafati; David C. Noelle (KEG@AAAI, 2019)

Learning Representations in Model-Free Hierarchical Reinforcement Learning. - Jacob Rafati; David C. Noelle (AAAI, 2019)

Do Humans Look Where Deep Convolutional Neural Networks "Attend"? - Mohammad K. Ebrahimpour; J. Benjamin Falandays; Samuel Spevack; David C. Noelle (ISVC (2), 2019)

Fast Object Localization via Sensitivity Analysis. - Mohammad K. Ebrahimpour; David C. Noelle (ISVC (2), 2019)

Ventral-Dorsal Neural Networks: Object Detection Via Selective Attention. - Mohammad K. Ebrahimpour; Jiayun Li; Yen-Yun Yu; Jackson Reesee; Azadeh Moghtaderi; Ming-Hsuan Yang 001; David C. Noelle (WACV, 2019)

Affordance Compatibility Effect for Word Learning in Virtual Reality. - Chelsea Gordon; Timothy M. Shea; David C. Noelle; Ramesh Balasubramaniam (Cogn. Sci., 2019)

Learning sparse representations in reinforcement learning. - Jacob Rafati; David C. Noelle (CoRR, 2019)

Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning. - Jacob Rafati; David C. Noelle (CoRR, 2019)

End-To-End Auditory Object Recognition Via Inception Nucleus. - Mohammad K. Ebrahimpour; Timothy M. Shea; Andreea Danielescu 001; David C. Noelle; Christopher T. Kello (ICASSP, 2020)

WW-Nets: Dual Neural Networks for Object Detection. - Mohammad K. Ebrahimpour; J. Benjamin Falandays; Samuel Spevack; Ming-Hsuan Yang 001; David C. Noelle (IJCNN, 2020)

Ventral-Dorsal Neural Networks: Object Detection via Selective Attention. - Mohammad K. Ebrahimpour; Jiayun Li; Yen-Yun Yu; Jackson L. Reese; Azadeh Moghtaderi; Ming-Hsuan Yang 001; David C. Noelle (CoRR, 2020)

InfantNet: A Deep Neural Network for Analyzing Infant Vocalizations. - Mohammad K. Ebrahimpour; Sara Schneider; David C. Noelle; Christopher T. Kello (CoRR, 2020)

Introduction to Progress and Puzzles of Cognitive Science. - Rick Dale; Ruth M. J. Byrne; Emma Cohen; Ophelia Deroy; Samuel J. Gershman; Janet H. Hsiao; Ping Li 026; Padraic Monaghan; David C. Noelle; Iris van Rooij; Priti Shah; Michael J. Spivey; et al. (Cogn. Sci., 2024)