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ORCIDDavid C. Noelle
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- affiliation: University of California, Merced, CA, USA
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2020 – today
- 2024
[j6]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)- 2020
- [c34]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: 146-150 - [c33]Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, Ming-Hsuan Yang, David C. Noelle:
WW-Nets: Dual Neural Networks for Object Detection. IJCNN 2020: 1-8 - [i8]Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, Ming-Hsuan Yang, David C. Noelle:
WW-Nets: Dual Neural Networks for Object Detection. CoRR abs/2005.07787 (2020) - [i7]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 abs/2005.09727 (2020) - [i6]Mohammad K. Ebrahimpour, Timothy M. Shea, Andreea Danielescu, David C. Noelle, Christopher T. Kello:
End-to-End Auditory Object Recognition via Inception Nucleus. CoRR abs/2005.12195 (2020) - [i5]Mohammad K. Ebrahimpour, Sara Schneider, David C. Noelle, Christopher T. Kello:
InfantNet: A Deep Neural Network for Analyzing Infant Vocalizations. CoRR abs/2005.12412 (2020)
2010 – 2019
- 2019
- [j5]Chelsea Gordon, Timothy M. Shea, David C. Noelle, Ramesh Balasubramaniam:
Affordance Compatibility Effect for Word Learning in Virtual Reality. Cogn. Sci. 43(6) (2019) - [c32]Jacob Rafati, David C. Noelle:
Unsupervised Methods For Subgoal Discovery During Intrinsic Motivation in Model-Free Hierarchical Reinforcement Learning. KEG@AAAI 2019: 17-25 - [c31]Jacob Rafati, David C. Noelle:
Learning Representations in Model-Free Hierarchical Reinforcement Learning. AAAI 2019: 10009-10010 - [c30]Mohammad K. Ebrahimpour, James Falandays, Samuel Spevack, David C. Noelle:
Do Humans Look Where Deep Convolutional Neural Networks "Attend"? CogSci 2019: 3448 - [c29]Mohammad K. Ebrahimpour, J. Benjamin Falandays, Samuel Spevack, David C. Noelle:
Do Humans Look Where Deep Convolutional Neural Networks "Attend"? ISVC (2) 2019: 53-65 - [c28]Mohammad K. Ebrahimpour, David C. Noelle:
Fast Object Localization via Sensitivity Analysis. ISVC (2) 2019: 209-220 - [c27]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: 986-994 - [i4]Jacob Rafati, David C. Noelle:
Learning sparse representations in reinforcement learning. CoRR abs/1909.01575 (2019) - [i3]Jacob Rafati, David C. Noelle:
Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning. CoRR abs/1911.10164 (2019) - 2018
- [c26]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 - [c25]Narjes Tahaei, David C. Noelle:
Automated Plagiarism Detection for Computer Programming Exercises Based on Patterns of Resubmission. ICER 2018: 178-186 - [i2]Jacob Rafati, David C. Noelle:
Learning Representations in Model-Free Hierarchical Reinforcement Learning. CoRR abs/1810.10096 (2018) - 2017
- [c24]David C. Noelle:
Indirection Explains Flexible Tuning of Neurons in Prefrontal Cortex. CogSci 2017 - 2016
- [c23]David C. Noelle:
Toward a Simulation Platform for Comparing Computational Cognitive Neuroscience Models. CogSci 2016 - 2015
- [j4]William Benjamin St. Clair, David C. Noelle:
Implications of polychronous neuronal groups for the continuity of mind. Cogn. Process. 16(4): 319-323 (2015) - [c22]William Benjamin St. Clair, David C. Noelle:
Topological Dependence of Rate Code Stability. CogSci 2015 - [c21]Angelo Kyrilov, David C. Noelle:
A Case-Based Reasoning Approach to Providing High-Quality Feedback on Computer Programming Exercises. CogSci 2015 - [c20]Jacob Rafati, David C. Noelle:
Lateral Inhibition Overcomes Limits of Temporal Difference Learning. CogSci 2015 - [c19]Jeffrey Rodny, David C. Noelle:
Modeling the Role of Hippocampus in Extinction and Spontaneous Recovery. CogSci 2015 - [c18]Timothy M. Shea, Anne S. Warlaumont, Christopher T. Kello, David C. Noelle:
Neuronal Dynamics and Spatial Foraging. CogSci 2015 - [c17]Angelo Kyrilov, David C. Noelle:
Binary instant feedback on programming exercises can reduce student engagement and promote cheating. Koli Calling 2015: 122-126 - [e1]David C. Noelle, Rick Dale, Anne S. Warlaumont, Jeff Yoshimi, Teenie Matlock, Carolyn D. Jennings, Paul P. Maglio:
Proceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015, Pasadena, California, USA, July 22-25, 2015. cognitivesciencesociety.org 2015, ISBN 978-0-9911967-2-2 [contents] - [i1]Angelo Kyrilov, David C. Noelle:
Using Automated Theorem Provers to Teach Knowledge Representation in First-Order Logic. CoRR abs/1507.03670 (2015) - 2014
- [c16]David C. Noelle, Justin Ray:
Robotic Learning Of The Delayed Saccade Task Using A Neurally Inspired Adaptive Working Memory System. CogSci 2014 - 2013
- [c15]William Benjamin St. Clair, David C. Noelle:
Implications of Polychronous Neuronal Groups for the Nature of Mental Representations. CogSci 2013 - [c14]Jeffrey Rodny, David C. Noelle:
Approximating the Value Function in the Actor Critic Architecture using the Temporal Dynamics of Spiking Neural Networks. CogSci 2013 - [c13]Angelo Kyrilov, David C. Noelle:
Automatic formative assessment of exercises on knowledge representation in first-order logic. ITiCSE 2013: 343 - 2011
- [j3]Trent Kriete, David C. Noelle:
Generalisation benefits of output gating in a model of prefrontal cortex. Connect. Sci. 23(2): 119-129 (2011) - [j2]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A dual association model for the extinction of animal conditioning. Neurocomputing 74(17): 3531-3542 (2011) - [j1]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A Cognitive Model for Generalization during Sequential Learning. J. Robotics 2011: 617613:1-617613:12 (2011) - [c12]David C. Noelle:
Interacting Complementary Learning Systems in Brains and Machines. BICA 2011: 262 - [c11]Antonio Chella, Christian Lebiere, David C. Noelle, Alexei V. Samsonovich:
On a Roadmap to Biologically Inspired Cognitive Agents. BICA 2011: 453-460 - [c10]William Benjamin St. Clair, David C. Noelle:
Asymmetric Intercortical Projections Support The Learning Of Temporal Associations. CogSci 2011
2000 – 2009
- 2009
- [c9]Alexei V. Samsonovich, David C. Noelle, Shane T. Mueller:
Preface. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2009 - 2008
- [c8]David C. Noelle:
Function Follows Form: Biologically Guided Functional Decomposition of Memory Systems. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2008: 135-139 - 2007
- [c7]Ashish Gupta, David C. Noelle:
A Dual-Pathway Neural Network Model of Control Relinquishment in Motor Skill Learning. IJCAI 2007: 405-410 - 2005
- [c6]Ashish Gupta, David C. Noelle:
Neurocomputational Mechanisms for Generalization During the Sequential Learning of Multiple Tasks. IICAI 2005: 2699-2711 - [c5]Joshua L. Phillips, David C. Noelle:
A biologically inspired working memory framework for robots. RO-MAN 2005: 599-604 - [c4]D. Mitchell Wilkes, Mert Tugcu, Jonathan E. Hunter, David C. Noelle:
Working memory and perception. RO-MAN 2005: 686-691 - 2004
- [c3]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: 68-75
1990 – 1999
- 1996
- [c2]David C. Noelle:
A Connectionist Model of Instructed Learning. AAAI/IAAI, Vol. 2 1996: 1368 - 1994
- [c1]David C. Noelle, Garrison W. Cottrell:
Integrating Induction & Instruction: Connectionist Advice Taking. AAAI 1994: 1481
Coauthor Index
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