James L. McClelland

Orcid: 0000-0002-8217-405X

Affiliations:
  • Stanford University, USA


According to our database1, James L. McClelland authored at least 74 papers between 1985 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
SODA: Bottleneck Diffusion Models for Representation Learning.
CoRR, 2023

Causal interventions expose implicit situation models for commonsense language understanding.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
A weighted constraint satisfaction approach to human goal-directed decision making.
PLoS Comput. Biol., 2022

Out-of-Distribution Generalization in Algorithmic Reasoning Through Curriculum Learning.
CoRR, 2022

Learning to Reason With Relational Abstractions.
CoRR, 2022

Systematic Generalization and Emergent Structures in Transformers Trained on Structured Tasks.
CoRR, 2022

Language models show human-like content effects on reasoning.
CoRR, 2022

Data Distributional Properties Drive Emergent In-Context Learning in Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Tell me why! Explanations support learning relational and causal structure.
Proceedings of the International Conference on Machine Learning, 2022

Can language models learn from explanations in context?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
What underlies rapid learning and systematic generalization in humans.
CoRR, 2021

Are people still smarter than machines? If so, why?
Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020
Transforming task representations to perform novel tasks.
Proc. Natl. Acad. Sci. USA, 2020

Transforming task representations to allow deep learning models to perform novel tasks.
CoRR, 2020

Emerging Representations for Counting in a Neural Network Agent Interacting with a Multimodal Environment.
Proceedings of the 2020 Conference on Artificial Life, 2020

Environmental drivers of systematicity and generalization in a situated agent.
Proceedings of the 8th International Conference on Learning Representations, 2020

Human-like learning Framework for frequency-skewed multi-level classification.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

A computational model of learning to count in a multimodal, interactive environment.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

Cognitive consequences of structured education in a connectionist model of analogical reasoning.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

Generative Continual Concept Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Developing the knowledge of number digits in a child-like robot.
Nat. Mach. Intell., 2019

Extending Machine Language Models toward Human-Level Language Understanding.
CoRR, 2019

Emergent Systematic Generalization in a Situated Agent.
CoRR, 2019

Embedded Meta-Learning: Toward more flexible deep-learning models.
CoRR, 2019

Modeling Number Sense Acquisition in A Number Board Game by Coordinating Verbal, Visual, and Grounded Action Components.
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Symposium in Memory of Jeff Elman: Language Learning, Prediction, and Temporal Dynamics.
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018
Distinct Representations of Magnitude and Spatial Position within Parietal Cortex during Number-Space Mapping.
J. Cogn. Neurosci., 2018

A mathematical theory of semantic development in deep neural networks.
CoRR, 2018

Can a Recurrent Neural Network Learn to Count Things?
Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

Can Generic Neural Networks Estimate Numerosity Like Humans?
Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017
One-shot and few-shot learning of word embeddings.
CoRR, 2017

Neural responses decrease while performance increases with practice: A neural network model.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Analogies Emerge from Learning Dyamics in Neural Networks.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Geometric Concept Acquisition in a Dueling Deep Q-Network.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016
Emergence of Euclidean geometrical intuitions in hierarchical generative models.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

N400 amplitudes reflect change in a probabilistic representation of meaning: Evidence from a connectionist model.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Tutorial Workshop on Contemporary Deep Neural Network Models.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015
Connecting learning, memory, and representation in math education.
Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition.
Cogn. Sci., 2014

Interactive Activation and Mutual Constraint Satisfaction in Perception and Cognition.
Cogn. Sci., 2014

A neural network model of learning mathematical equivalence.
Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

Two Plus Three Is Five: Discovering Efficient Addition Strategies without Metacognition.
Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2013
Why Bilateral Damage Is Worse than Unilateral Damage to the Brain.
J. Cogn. Neurosci., 2013

A Differentiation Account of Recognition Memory: Evidence from fMRI.
J. Cogn. Neurosci., 2013

Progressive Development of the Number Sense in a Deep Neural Network.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Learning hierarchical categories in deep neural networks.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Running circles around symbol manipulation in trigonometry.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

From symbols to analog magnitudes: A process model of fraction comparison, with fits to experimental data.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2011
Predicting native English-like performance by native Japanese speakers.
J. Phonetics, 2011

A PDP model of the simultaneous perception of multiple objects.
Connect. Sci., 2011

Estimating the strength of unlabeled information during semi-supervised learning.
Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010
Emergence in Cognitive Science.
Top. Cogn. Sci., 2010

Cognitive Science Meets Autonomous Mental Development.
Cogn. Sci., 2010

2009
The Place of Modeling in Cognitive Science.
Top. Cogn. Sci., 2009

Modeling Unsupervised Perceptual Category Learning.
IEEE Trans. Auton. Ment. Dev., 2009

Is a Machine Realization of Truly Human-Like Intelligence Achievable?
Cogn. Comput., 2009

2008
Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms.
Cogn. Sci., 2008

2007
Guest Editorial: Convergent Approaches to the Understanding of Autonomous Mental Development.
IEEE Trans. Evol. Comput., 2007

2006
Performance Feedback Drives Caudate Activation in a Phonological Learning Task.
J. Cogn. Neurosci., 2006

2005
Dissociating Reading Processes on the Basis of Neuronal Interactions.
J. Cogn. Neurosci., 2005

2000
Normal and impaired processing in quasi-regular domains of language: the case of English past-tense verbs.
Proceedings of the Sixth International Conference on Spoken Language Processing, 2000

1999
Information Factorization in Connectionist Models of Perception.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1997
A Hippocampal Model of Recognition Memory.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1993
Learning Continuous Probability Distributions with Symmetric Diffusion Networks.
Cogn. Sci., 1993

1991
Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks.
Mach. Learn., 1991

1990
Learning and Applying Contextual Constraints in Sentence Comprehension.
Artif. Intell., 1990

Distributed Representations.
Proceedings of the Philosophy of Artificial Intelligence., 1990

1989
Finite State Automata and Simple Recurrent Networks.
Neural Comput., 1989

Connectionist Models of Language.
Proceedings of the First International Workshop on Parsing Technologies, 1989

1988
Learning Subsequential Structure in Simple Recurrent Networks.
Proceedings of the Advances in Neural Information Processing Systems 1, 1988

1987
Parallel Distributed Processing and Role Assignment Constraints.
Proceedings of the Theoretical Issues in Natural Language Processing 3, 1987

Learning Representations by Recirculation.
Proceedings of the Neural Information Processing Systems, Denver, Colorado, USA, 1987, 1987

1985
Putting Knowledge in its Place: A Scheme for Programming Parallel Processing Structures on the Fly.
Cogn. Sci., 1985


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