David C. Noelle

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 21

Top Topics

Lateral Inhibition

Hierarchical Reinforcement Learning

Programming Exercises

Object Detection

Top Venues

Publications

Rick Dale, Ruth M. J. Byrne, Emma Cohen, Ophelia Deroy, Samuel J. Gershman, Janet H. Hsiao, Ping Li, Padraic Monaghan, David C. Noelle, Iris van Rooij, Priti Shah, Michael J. Spivey, Sashank Varma
Introduction to Progress and Puzzles of Cognitive Science. Cogn. Sci. 48 (7) (2024)
Mohammad K. Ebrahimpour, Timothy M. Shea, Andreea Danielescu, David C. Noelle, Christopher T. Kello
End-To-End Auditory Object Recognition Via Inception Nucleus. ICASSP (2020)
Mohammad K. Ebrahimpour, Jiayun Li, Yen-Yun Yu, Jackson L. Reese, Azadeh Moghtaderi, Ming-Hsuan Yang, David C. Noelle
Ventral-Dorsal Neural Networks: Object Detection via Selective Attention. CoRR (2020)
Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, Ming-Hsuan Yang, David C. Noelle
WW-Nets: Dual Neural Networks for Object Detection. CoRR (2020)
Mohammad K. Ebrahimpour, Sara Schneider, David C. Noelle, Christopher T. Kello
InfantNet: A Deep Neural Network for Analyzing Infant Vocalizations. CoRR (2020)
Mohammad K. Ebrahimpour, Timothy M. Shea, Andreea Danielescu, David C. Noelle, Christopher T. Kello
End-to-End Auditory Object Recognition via Inception Nucleus. CoRR (2020)
Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, Ming-Hsuan Yang, David C. Noelle
WW-Nets: Dual Neural Networks for Object Detection. IJCNN (2020)
Jacob Rafati, David C. Noelle
Unsupervised Methods For Subgoal Discovery During Intrinsic Motivation in Model-Free Hierarchical Reinforcement Learning. KEG@AAAI (2019)
Jacob Rafati, David C. Noelle
Learning sparse representations in reinforcement learning. CoRR (2019)
Mohammad K. Ebrahimpour, Jiayun Li, Yen-Yun Yu, Jackson Reesee, Azadeh Moghtaderi, Ming-Hsuan Yang, David C. Noelle
Ventral-Dorsal Neural Networks: Object Detection Via Selective Attention. WACV (2019)
Chelsea Gordon, Timothy M. Shea, David C. Noelle, Ramesh Balasubramaniam
Affordance Compatibility Effect for Word Learning in Virtual Reality. Cogn. Sci. 43 (6) (2019)
Mohammad K. Ebrahimpour, David C. Noelle
Fast Object Localization via Sensitivity Analysis. ISVC (2) (2019)
Jacob Rafati, David C. Noelle
Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning. CoRR (2019)
Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, David C. Noelle
Do Humans Look Where Deep Convolutional Neural Networks "Attend"? ISVC (2) (2019)
Mohammad K. Ebrahimpour, James Falandays, Samuel Spevack, David C. Noelle
Do Humans Look Where Deep Convolutional Neural Networks "Attend"? CogSci (2019)
Jacob Rafati, David C. Noelle
Learning Representations in Model-Free Hierarchical Reinforcement Learning. AAAI (2019)
Timothy M. Shea, David C. Noelle
A Conceptual Ladder from Spikes to Behavior: Toward the Neural Basis of Dynamic Choices at Multiple Scales. CogSci (2018)
Narjes Tahaei, David C. Noelle
Automated Plagiarism Detection for Computer Programming Exercises Based on Patterns of Resubmission. ICER (2018)
Jacob Rafati, David C. Noelle
Learning Representations in Model-Free Hierarchical Reinforcement Learning. CoRR (2018)
David C. Noelle
Indirection Explains Flexible Tuning of Neurons in Prefrontal Cortex. CogSci (2017)
David C. Noelle
Toward a Simulation Platform for Comparing Computational Cognitive Neuroscience Models. CogSci (2016)
Angelo Kyrilov, David C. Noelle
Using Automated Theorem Provers to Teach Knowledge Representation in First-Order Logic. CoRR (2015)
William Benjamin St. Clair, David C. Noelle
Topological Dependence of Rate Code Stability. CogSci (2015)
Jacob Rafati, David C. Noelle
Lateral Inhibition Overcomes Limits of Temporal Difference Learning. CogSci (2015)
Angelo Kyrilov, David C. Noelle
Binary instant feedback on programming exercises can reduce student engagement and promote cheating. Koli Calling (2015)
Angelo Kyrilov, David C. Noelle
A Case-Based Reasoning Approach to Providing High-Quality Feedback on Computer Programming Exercises. CogSci (2015)
William Benjamin St. Clair, David C. Noelle
Implications of polychronous neuronal groups for the continuity of mind. Cogn. Process. 16 (4) (2015)
Timothy M. Shea, Anne S. Warlaumont, Christopher T. Kello, David C. Noelle
Neuronal Dynamics and Spatial Foraging. CogSci (2015)
Jeffrey Rodny, David C. Noelle
Modeling the Role of Hippocampus in Extinction and Spontaneous Recovery. CogSci (2015)
David C. Noelle, Justin Ray
Robotic Learning Of The Delayed Saccade Task Using A Neurally Inspired Adaptive Working Memory System. CogSci (2014)
William Benjamin St. Clair, David C. Noelle
Implications of Polychronous Neuronal Groups for the Nature of Mental Representations. CogSci (2013)
Jeffrey Rodny, David C. Noelle
Approximating the Value Function in the Actor Critic Architecture using the Temporal Dynamics of Spiking Neural Networks. CogSci (2013)
Angelo Kyrilov, David C. Noelle
Automatic formative assessment of exercises on knowledge representation in first-order logic. ITiCSE (2013)
Trent Kriete, David C. Noelle
Generalisation benefits of output gating in a model of prefrontal cortex. Connect. Sci. 23 (2) (2011)
William Benjamin St. Clair, David C. Noelle
Asymmetric Intercortical Projections Support The Learning Of Temporal Associations. CogSci (2011)
David C. Noelle
Interacting Complementary Learning Systems in Brains and Machines. BICA (2011)
Antonio Chella, Christian Lebiere, David C. Noelle, Alexei V. Samsonovich
On a Roadmap to Biologically Inspired Cognitive Agents. BICA (2011)
Ashish Gupta, Lovekesh Vig, David C. Noelle
A Cognitive Model for Generalization during Sequential Learning. J. Robotics 2011 (2011)
Ashish Gupta, Lovekesh Vig, David C. Noelle
A dual association model for the extinction of animal conditioning. Neurocomputing 74 (17) (2011)
Alexei V. Samsonovich, David C. Noelle, Shane T. Mueller
Preface. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures (2009)
David C. Noelle
Function Follows Form: Biologically Guided Functional Decomposition of Memory Systems. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures (2008)
Ashish Gupta, David C. Noelle
A Dual-Pathway Neural Network Model of Control Relinquishment in Motor Skill Learning. IJCAI (2007)
D. Mitchell Wilkes, Mert Tugcu, Jonathan E. Hunter, David C. Noelle
Working memory and perception. RO-MAN (2005)
Ashish Gupta, David C. Noelle
Neurocomputational Mechanisms for Generalization During the Sequential Learning of Multiple Tasks. IICAI (2005)
Joshua L. Phillips, David C. Noelle
A biologically inspired working memory framework for robots. RO-MAN (2005)
Marjorie Skubic, David C. Noelle, D. Mitch Wilkes, Kazuhiko Kawamura, James M. Keller
A Biologically Inspired Adaptive Working Memory for Robots. AAAI Technical Report (5) (2004)
David C. Noelle
A Connectionist Model of Instructed Learning. AAAI/IAAI, Vol. 2 (1996)
David C. Noelle, Garrison W. Cottrell
Integrating Induction & Instruction: Connectionist Advice Taking. AAAI (1994)