James L. McClelland

78 papers A* 5A 1B 14C 1Journal 47Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Emergent Symbol-like Number Variables in Artificial Neural Networks. CoRR Satchel Grant, Noah D. Goodman, James L. McClelland
2025	J	`jnl`	Emergent Symbol-like Number Variables in Artificial Neural Networks. Trans. Mach. Learn. Res. Satchel Grant, Noah Goodman, James L. McClelland
2025	J	`jnl`	Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences. CoRR Andrew Kyle Lampinen, Martin Engelcke, Yuxuan Li, Arslan Chaudhry, James L. McClelland
2025	J	`jnl`	Modeling Language as a Sequence of Thoughts. CoRR Nasim Borazjanizadeh, James L. McClelland
2025	J	`jnl`	Neural Computation Without Slots: Steps Towards Biologically Plausible Memory and Attention in Natural and Artificial Intelligence. CoRR Shaunak Bhandarkar, James L. McClelland
2025	J	`jnl`	On the generalization of language models from in-context learning and finetuning: a controlled study. CoRR Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland
2025	J	`jnl`	Reflections on David E. Rumelhart and the Rumelhart Prize. Top. Cogn. Sci. James L. McClelland
2024	A*	`conf`	SODA: Bottleneck Diffusion Models for Representation Learning. CVPR Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner
2023	—	`conf`	Causal interventions expose implicit situation models for commonsense language understanding. ACL (Findings) Takateru Yamakoshi, James L. McClelland, Adele Goldberg, Robert D. Hawkins
2023	J	`jnl`	Causal interventions expose implicit situation models for commonsense language understanding. CoRR Takateru Yamakoshi, James L. McClelland, Adele E. Goldberg, Robert D. Hawkins
2023	J	`jnl`	Representations and Computations in Transformers that Support Generalization on Structured Tasks. Trans. Mach. Learn. Res. Yuxuan Li, James L. McClelland
2023	J	`jnl`	SODA: Bottleneck Diffusion Models for Representation Learning. CoRR Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner
2022	J	`jnl`	A weighted constraint satisfaction approach to human goal-directed decision making. PLoS Comput. Biol. Yuxuan Li, James L. McClelland
2022	—	`conf`	Can language models learn from explanations in context? EMNLP (Findings) Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill
2022	J	`jnl`	Can language models learn from explanations in context? CoRR Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane X. Wang, Felix Hill
2022	A*	`conf`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. NeurIPS Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill
2022	J	`jnl`	Language models show human-like content effects on reasoning. CoRR Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill
2022	J	`jnl`	Learning to Reason With Relational Abstractions. CoRR Andrew Joohun Nam, Mengye Ren, Chelsea Finn, James L. McClelland
2022	J	`jnl`	Out-of-Distribution Generalization in Algorithmic Reasoning Through Curriculum Learning. CoRR Andrew Joohun Nam, Mustafa Abdool, Trevor Maxfield, James L. McClelland
2022	J	`jnl`	Systematic Generalization and Emergent Structures in Transformers Trained on Structured Tasks. CoRR Yuxuan Li, James L. McClelland
2022	A*	`conf`	Tell me why! Explanations support learning relational and causal structure. ICML Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill
2021	J	`jnl`	Tell me why! - Explanations support learning of relational and causal structure. CoRR Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill
2021	J	`jnl`	What underlies rapid learning and systematic generalization in humans. CoRR Andrew Joohun Nam, James L. McClelland
2020	C	`conf`	Emerging Representations for Counting in a Neural Network Agent Interacting with a Multimodal Environment. ALIFE Silvester Sabathiel, James L. McClelland, Trygve Solstad
2020	A*	`conf`	Environmental drivers of systematicity and generalization in a situated agent. ICLR Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro
2020	A*	`conf`	Generative Continual Concept Learning. AAAI Mohammad Rostami, Soheil Kolouri, Praveen K. Pilly, James L. McClelland
2020	J	`jnl`	Transforming task representations to allow deep learning models to perform novel tasks. CoRR Andrew K. Lampinen, James L. McClelland
2020	J	`jnl`	Transforming task representations to perform novel tasks. Proc. Natl. Acad. Sci. USA Andrew K. Lampinen, James L. McClelland
2019	J	`jnl`	Developing the knowledge of number digits in a child-like robot. Nat. Mach. Intell. Alessandro G. Di Nuovo, James L. McClelland
2019	J	`jnl`	Embedded Meta-Learning: Toward more flexible deep-learning models. CoRR Andrew K. Lampinen, James L. McClelland
2019	J	`jnl`	Emergent Systematic Generalization in a Situated Agent. CoRR Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro
2019	J	`jnl`	Extending Machine Language Models toward Human-Level Language Understanding. CoRR James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
2019	J	`jnl`	Generative Continual Concept Learning. CoRR Mohammad Rostami, Soheil Kolouri, James L. McClelland, Praveen K. Pilly
2018	J	`jnl`	A mathematical theory of semantic development in deep neural networks. CoRR Andrew M. Saxe, James L. McClelland, Surya Ganguli
2018	J	`jnl`	Distinct Representations of Magnitude and Spatial Position within Parietal Cortex during Number-Space Mapping. J. Cogn. Neurosci. Frank J. Kanayet, Andrew Mattarella-Micke, Peter J. Kohler, Anthony M. Norcia, Bruce D. McCandliss, James L. McClelland
2017	B	`conf`	Analogies Emerge from Learning Dyamics in Neural Networks. CogSci Andrew K. Lampinen, Shaw Hsu, James L. McClelland
2017	B	`conf`	Geometric Concept Acquisition in a Dueling Deep Q-Network. CogSci Alex Kuefler, Mykel J. Kochenderfer, James L. McClelland
2017	B	`conf`	Neural responses decrease while performance increases with practice: A neural network model. CogSci Milena Rabovsky, Steven Stenberg Hansen, James L. McClelland
2017	J	`jnl`	One-shot and few-shot learning of word embeddings. CoRR Andrew K. Lampinen, James L. McClelland
2016	B	`conf`	Emergence of Euclidean geometrical intuitions in hierarchical generative models. CogSci Arianna Yuan, Te-Lin Wu, James L. McClelland
2016	B	`conf`	N400 amplitudes reflect change in a probabilistic representation of meaning: Evidence from a connectionist model. CogSci Milena Rabovsky, Steven Stenberg Hansen, James L. McClelland
2016	B	`conf`	Tutorial Workshop on Contemporary Deep Neural Network Models. CogSci James L. McClelland, Steven Stenberg Hansen, Andrew M. Saxe
2015	B	`conf`	Connecting learning, memory, and representation in math education. CogSci Martha W. Alibali, Chuck Kalish, Timothy T. Rogers, Christine M. Massey, Philip J. Kellman, Vladimir M. Sloutsky, James L. McClelland, Kevin W. Mickey
2014	B	`conf`	A neural network model of learning mathematical equivalence. CogSci Kevin W. Mickey, James L. McClelland
2014	—	`conf`	Exact solutions to the nonlinear dynamics of learning in deep linear neural networks. ICLR Andrew M. Saxe, James L. McClelland, Surya Ganguli
2014	J	`jnl`	Interactive Activation and Mutual Constraint Satisfaction in Perception and Cognition. Cogn. Sci. James L. McClelland, Daniel Mirman, Donald J. Bolger, Pranav Khaitan
2014	J	`jnl`	Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition. Cogn. Sci. Timothy T. Rogers, James L. McClelland
2014	B	`conf`	Two Plus Three Is Five: Discovering Efficient Addition Strategies without Metacognition. CogSci Steven Stenberg Hansen, Cameron R. L. McKenzie, James L. McClelland
2013	J	`jnl`	A Differentiation Account of Recognition Memory: Evidence from fMRI. J. Cogn. Neurosci. Amy H. Criss, Mark E. Wheeler, James L. McClelland
2013	B	`conf`	From symbols to analog magnitudes: A process model of fraction comparison, with fits to experimental data. CogSci Cameron R. L. McKenzie, James L. McClelland
2013	B	`conf`	Learning hierarchical categories in deep neural networks. CogSci Andrew M. Saxe, James L. McClelland, Surya Ganguli
2013	B	`conf`	Progressive Development of the Number Sense in a Deep Neural Network. CogSci Will Y. Zou, James L. McClelland
2013	B	`conf`	Running circles around symbol manipulation in trigonometry. CogSci Kevin W. Mickey, James L. McClelland
2013	J	`jnl`	Why Bilateral Damage Is Worse than Unilateral Damage to the Brain. J. Cogn. Neurosci. Anna C. Schapiro, James L. McClelland, Stephen R. Welbourne, Timothy T. Rogers, Matthew A. Lambon Ralph
2011	J	`jnl`	A PDP model of the simultaneous perception of multiple objects. Connect. Sci. Cynthia M. Henderson, James L. McClelland
2011	B	`conf`	Estimating the strength of unlabeled information during semi-supervised learning. CogSci Brenden M. Lake, James L. McClelland
2011	J	`jnl`	Predicting native English-like performance by native Japanese speakers. J. Phonetics Erin M. Ingvalson, James L. McClelland, Lori L. Holt
2010	J	`jnl`	Emergence in Cognitive Science. Top. Cogn. Sci. James L. McClelland
2009	J	`jnl`	Is a Machine Realization of Truly Human-Like Intelligence Achievable? Cogn. Comput. James L. McClelland
2009	J	`jnl`	Modeling Unsupervised Perceptual Category Learning. IEEE Trans. Auton. Ment. Dev. Brenden M. Lake, Gautam K. Vallabha, James L. McClelland
2009	J	`jnl`	The Place of Modeling in Cognitive Science. Top. Cogn. Sci. James L. McClelland
2008	J	`jnl`	Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms. Cogn. Sci. Daniel Mirman, James L. McClelland, Lori L. Holt, James S. Magnuson
2007	J	`jnl`	Guest Editorial: Convergent Approaches to the Understanding of Autonomous Mental Development. IEEE Trans. Evol. Comput. James L. McClelland, Kim Plunkett, Juyang Weng
2006	J	`jnl`	Performance Feedback Drives Caudate Activation in a Phonological Learning Task. J. Cogn. Neurosci. Elizabeth Tricomi, Mauricio R. Delgado, Bruce D. McCandliss, James L. McClelland, Julie A. Fiez
2005	J	`jnl`	Dissociating Reading Processes on the Basis of Neuronal Interactions. J. Cogn. Neurosci. Andrea Mechelli, Jennifer T. Crinion, Steven Long, Karl J. Friston, Matthew A. Lambon Ralph, Karalyn Patterson, James L. McClelland, Cathy J. Price
2000	A	`conf`	Normal and impaired processing in quasi-regular domains of language: the case of English past-tense verbs. INTERSPEECH Karalyn Patterson, Matthew A. Lambon Ralph, Helen Bird, John R. Hodges, James L. McClelland
1999	—	`conf`	Information Factorization in Connectionist Models of Perception. NIPS Javier R. Movellan, James L. McClelland
1997	—	`conf`	A Hippocampal Model of Recognition Memory. NIPS Randall C. O'Reilly, Kenneth A. Norman, James L. McClelland
1993	J	`jnl`	Learning Continuous Probability Distributions with Symmetric Diffusion Networks. Cogn. Sci. Javier R. Movellan, James L. McClelland
1991	J	`jnl`	Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks. Mach. Learn. David Servan-Schreiber, Axel Cleeremans, James L. McClelland
1990	—	`ch.`	Distributed Representations. The Philosophy of Artificial Intelligence Geoffrey E. Hinton, James L. McClelland, David E. Rumelhart
1990	J	`jnl`	Learning and Applying Contextual Constraints in Sentence Comprehension. Artif. Intell. Mark F. St. John, James L. McClelland
1989	—	`conf`	Connectionist Models of Language. IWPT James L. McClelland
1989	J	`jnl`	Finite State Automata and Simple Recurrent Networks. Neural Comput. Axel Cleeremans, David Servan-Schreiber, James L. McClelland
1988	—	`conf`	Learning Subsequential Structure in Simple Recurrent Networks. NIPS David Servan-Schreiber, Axel Cleeremans, James L. McClelland
1987	—	`conf`	Learning Representations by Recirculation. NIPS Geoffrey E. Hinton, James L. McClelland
1987	—	`conf`	Parallel Distributed Processing and Role Assignment Constraints. TINLAP James L. McClelland
1985	J	`jnl`	Putting Knowledge in its Place: A Scheme for Programming Parallel Processing Structures on the Fly. Cogn. Sci. James L. McClelland