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ORCIDJames L. McClelland
Jay McClelland
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- affiliation: Stanford University, USA
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2020 – today
- 2024
[c38]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CVPR 2024: 23115-23127- 2023
- [j25]Yuxuan Li, James L. McClelland:
Representations and Computations in Transformers that Support Generalization on Structured Tasks. Trans. Mach. Learn. Res. 2023 (2023) - [c37]Takateru Yamakoshi, James L. McClelland, Adele Goldberg, Robert D. Hawkins:
Causal interventions expose implicit situation models for commonsense language understanding. ACL (Findings) 2023: 13265-13293 - [i17]Takateru Yamakoshi, James L. McClelland, Adele E. Goldberg, Robert D. Hawkins:
Causal interventions expose implicit situation models for commonsense language understanding. CoRR abs/2306.03882 (2023) - [i16]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CoRR abs/2311.17901 (2023) - 2022
- [j24]Yuxuan Li
, James L. McClelland:
A weighted constraint satisfaction approach to human goal-directed decision making. PLoS Comput. Biol. 18(6) (2022) - [c36]Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill:
Can language models learn from explanations in context? EMNLP (Findings) 2022: 537-563 - [c35]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:
Tell me why! Explanations support learning relational and causal structure. ICML 2022: 11868-11890 - [c34]Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill:
Data Distributional Properties Drive Emergent In-Context Learning in Transformers. NeurIPS 2022 - [i15]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:
Can language models learn from explanations in context? CoRR abs/2204.02329 (2022) - [i14]Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill:
Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR abs/2205.05055 (2022) - [i13]Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill:
Language models show human-like content effects on reasoning. CoRR abs/2207.07051 (2022) - [i12]Yuxuan Li, James L. McClelland:
Systematic Generalization and Emergent Structures in Transformers Trained on Structured Tasks. CoRR abs/2210.00400 (2022) - [i11]Andrew Joohun Nam, Mengye Ren, Chelsea Finn, James L. McClelland:
Learning to Reason With Relational Abstractions. CoRR abs/2210.02615 (2022) - [i10]Andrew Joohun Nam, Mustafa Abdool, Trevor Maxfield, James L. McClelland:
Out-of-Distribution Generalization in Algorithmic Reasoning Through Curriculum Learning. CoRR abs/2210.03275 (2022) - 2021
- [c33]Jay McClelland:
Are people still smarter than machines? If so, why? CogSci 2021 - [i9]Andrew Joohun Nam, James L. McClelland:
What underlies rapid learning and systematic generalization in humans. CoRR abs/2107.06994 (2021) - [i8]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:
Tell me why! - Explanations support learning of relational and causal structure. CoRR abs/2112.03753 (2021) - 2020
- [j23]Andrew K. Lampinen, James L. McClelland:
Transforming task representations to perform novel tasks. Proc. Natl. Acad. Sci. USA 117(52): 32970-32981 (2020) - [c32]Mohammad Rostami, Soheil Kolouri, Praveen K. Pilly, James L. McClelland:
Generative Continual Concept Learning. AAAI 2020: 5545-5552 - [c31]David Barrett, Felix Hill, Adam Santoro, Jay McClelland:
Cognitive consequences of structured education in a connectionist model of analogical reasoning. CogSci 2020 - [c30]Silvester Sabathiel, Jay McClelland, Trygve Solstad:
A computational model of learning to count in a multimodal, interactive environment. CogSci 2020 - [c29]Amarjot Singh, Jay McClelland:
Human-like learning Framework for frequency-skewed multi-level classification. CogSci 2020 - [c28]Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro:
Environmental drivers of systematicity and generalization in a situated agent. ICLR 2020 - [c27]Silvester Sabathiel, James L. McClelland, Trygve Solstad:
Emerging Representations for Counting in a Neural Network Agent Interacting with a Multimodal Environment. ALIFE 2020: 736-743 - [i7]Andrew K. Lampinen, James L. McClelland:
Transforming task representations to allow deep learning models to perform novel tasks. CoRR abs/2005.04318 (2020)
2010 – 2019
- 2019
- [j22]Alessandro G. Di Nuovo, James L. McClelland:
Developing the knowledge of number digits in a child-like robot. Nat. Mach. Intell. 1(12): 594-605 (2019) - [c26]Jay McClelland, Ken McRae:
Symposium in Memory of Jeff Elman: Language Learning, Prediction, and Temporal Dynamics. CogSci 2019: 33-34 - [c25]Arianna Yuan, Jay McClelland:
Modeling Number Sense Acquisition in A Number Board Game by Coordinating Verbal, Visual, and Grounded Action Components. CogSci 2019: 3186-3192 - [i6]Andrew K. Lampinen, James L. McClelland:
Embedded Meta-Learning: Toward more flexible deep-learning models. CoRR abs/1905.09950 (2019) - [i5]Mohammad Rostami, Soheil Kolouri, James L. McClelland, Praveen K. Pilly:
Generative Continual Concept Learning. CoRR abs/1906.03744 (2019) - [i4]Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro:
Emergent Systematic Generalization in a Situated Agent. CoRR abs/1910.00571 (2019) - [i3]James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze:
Extending Machine Language Models toward Human-Level Language Understanding. CoRR abs/1912.05877 (2019) - 2018
- [j21]Frank J. Kanayet, Andrew Mattarella-Micke, Peter J. Kohler, Anthony M. Norcia, Bruce D. McCandliss, James L. McClelland:
Distinct Representations of Magnitude and Spatial Position within Parietal Cortex during Number-Space Mapping. J. Cogn. Neurosci. 30(2) (2018) - [c24]Sharon Chen, Zhenglong Zhou, Mengting Fang, Jay McClelland:
Can Generic Neural Networks Estimate Numerosity Like Humans? CogSci 2018 - [c23]Mengting Fang, Zhenglong Zhou, Sharon Chen, Jay McClelland:
Can a Recurrent Neural Network Learn to Count Things? CogSci 2018 - [i2]Andrew M. Saxe, James L. McClelland, Surya Ganguli:
A mathematical theory of semantic development in deep neural networks. CoRR abs/1810.10531 (2018) - 2017
- [c22]Alex Kuefler, Mykel J. Kochenderfer, James L. McClelland:
Geometric Concept Acquisition in a Dueling Deep Q-Network. CogSci 2017 - [c21]Andrew K. Lampinen, Shaw Hsu, James L. McClelland:
Analogies Emerge from Learning Dyamics in Neural Networks. CogSci 2017 - [c20]Milena Rabovsky, Steven Stenberg Hansen, James L. McClelland:
Neural responses decrease while performance increases with practice: A neural network model. CogSci 2017 - [i1]Andrew K. Lampinen, James L. McClelland:
One-shot and few-shot learning of word embeddings. CoRR abs/1710.10280 (2017) - 2016
- [c19]James L. McClelland, Steven Stenberg Hansen, Andrew M. Saxe:
Tutorial Workshop on Contemporary Deep Neural Network Models. CogSci 2016 - [c18]Milena Rabovsky, Steven Stenberg Hansen, James L. McClelland:
N400 amplitudes reflect change in a probabilistic representation of meaning: Evidence from a connectionist model. CogSci 2016 - [c17]Arianna Yuan, Te-Lin Wu, James L. McClelland:
Emergence of Euclidean geometrical intuitions in hierarchical generative models. CogSci 2016 - 2015
- [c16]Martha W. Alibali, Chuck Kalish, Timothy T. Rogers, Christine M. Massey, Philip J. Kellman, Vladimir M. Sloutsky, James L. McClelland, Kevin W. Mickey:
Connecting learning, memory, and representation in math education. CogSci 2015 - 2014
- [j20]Timothy T. Rogers, James L. McClelland:
Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition. Cogn. Sci. 38(6): 1024-1077 (2014) - [j19]James L. McClelland, Daniel Mirman, Donald J. Bolger, Pranav Khaitan:
Interactive Activation and Mutual Constraint Satisfaction in Perception and Cognition. Cogn. Sci. 38(6): 1139-1189 (2014) - [c15]Steven Stenberg Hansen, Cameron R. L. McKenzie, James L. McClelland:
Two Plus Three Is Five: Discovering Efficient Addition Strategies without Metacognition. CogSci 2014 - [c14]Kevin W. Mickey, James L. McClelland:
A neural network model of learning mathematical equivalence. CogSci 2014 - [c13]Andrew M. Saxe, James L. McClelland, Surya Ganguli:
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks. ICLR 2014 - 2013
- [j18]Amy H. Criss, Mark E. Wheeler, James L. McClelland:
A Differentiation Account of Recognition Memory: Evidence from fMRI. J. Cogn. Neurosci. 25(3): 421-435 (2013) - [j17]Anna C. Schapiro, James L. McClelland, Stephen R. Welbourne, Timothy T. Rogers, Matthew A. Lambon Ralph:
Why Bilateral Damage Is Worse than Unilateral Damage to the Brain. J. Cogn. Neurosci. 25(12): 2107-2123 (2013) - [c12]Cameron R. L. McKenzie, James L. McClelland:
From symbols to analog magnitudes: A process model of fraction comparison, with fits to experimental data. CogSci 2013 - [c11]Kevin W. Mickey, James L. McClelland:
Running circles around symbol manipulation in trigonometry. CogSci 2013 - [c10]Andrew M. Saxe, James L. McClelland, Surya Ganguli:
Learning hierarchical categories in deep neural networks. CogSci 2013 - [c9]Will Y. Zou, James L. McClelland:
Progressive Development of the Number Sense in a Deep Neural Network. CogSci 2013 - 2011
- [j16]Cynthia M. Henderson, James L. McClelland:
A PDP model of the simultaneous perception of multiple objects. Connect. Sci. 23(2): 161-172 (2011) - [j15]Erin M. Ingvalson, James L. McClelland, Lori L. Holt:
Predicting native English-like performance by native Japanese speakers. J. Phonetics 39(4): 571-584 (2011) - [c8]Brenden M. Lake, James L. McClelland:
Estimating the strength of unlabeled information during semi-supervised learning. CogSci 2011 - 2010
- [j14]Jay McClelland, Juyang Weng, Gedeon O. Deák, Brian Scassellati:
Cognitive Science Meets Autonomous Mental Development. Cogn. Sci. 34(3): 533-534 (2010) - [j13]James L. McClelland:
Emergence in Cognitive Science. Top. Cogn. Sci. 2(4): 751-770 (2010)
2000 – 2009
- 2009
- [j12]James L. McClelland:
Is a Machine Realization of Truly Human-Like Intelligence Achievable? Cogn. Comput. 1(1): 17-21 (2009) - [j11]Brenden M. Lake, Gautam K. Vallabha, James L. McClelland:
Modeling Unsupervised Perceptual Category Learning. IEEE Trans. Auton. Ment. Dev. 1(1): 35-43 (2009) - [j10]James L. McClelland:
The Place of Modeling in Cognitive Science. Top. Cogn. Sci. 1(1): 11-38 (2009) - 2008
- [j9]Daniel Mirman, James L. McClelland, Lori L. Holt, James S. Magnuson:
Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms. Cogn. Sci. 32(2): 398-417 (2008) - 2007
- [j8]James L. McClelland, Kim Plunkett, Juyang Weng:
Guest Editorial: Convergent Approaches to the Understanding of Autonomous Mental Development. IEEE Trans. Evol. Comput. 11(2): 133-136 (2007) - 2006
- [j7]Elizabeth Tricomi, Mauricio R. Delgado, Bruce D. McCandliss, James L. McClelland, Julie A. Fiez:
Performance Feedback Drives Caudate Activation in a Phonological Learning Task. J. Cogn. Neurosci. 18(6): 1029-1043 (2006) - 2005
- [j6]Andrea Mechelli, Jennifer T. Crinion, Steven Long, Karl J. Friston, Matthew A. Lambon Ralph, Karalyn Patterson, James L. McClelland, Cathy J. Price:
Dissociating Reading Processes on the Basis of Neuronal Interactions. J. Cogn. Neurosci. 17(11): 1753-1765 (2005) - 2000
- [c7]Karalyn Patterson, Matthew A. Lambon Ralph, Helen Bird, John R. Hodges, James L. McClelland:
Normal and impaired processing in quasi-regular domains of language: the case of English past-tense verbs. INTERSPEECH 2000: 15-19
1990 – 1999
- 1999
- [c6]Javier R. Movellan, James L. McClelland:
Information Factorization in Connectionist Models of Perception. NIPS 1999: 45-51 - 1997
- [c5]Randall C. O'Reilly, Kenneth A. Norman, James L. McClelland:
A Hippocampal Model of Recognition Memory. NIPS 1997: 73-79 - 1993
- [j5]Javier R. Movellan, James L. McClelland:
Learning Continuous Probability Distributions with Symmetric Diffusion Networks. Cogn. Sci. 17(4): 463-496 (1993) - 1991
- [j4]David Servan-Schreiber, Axel Cleeremans, James L. McClelland:
Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks. Mach. Learn. 7: 161-193 (1991) - 1990
- [j3]Mark F. St. John, James L. McClelland:
Learning and Applying Contextual Constraints in Sentence Comprehension. Artif. Intell. 46(1-2): 217-257 (1990) - [p1]Geoffrey E. Hinton, James L. McClelland, David E. Rumelhart:
Distributed Representations. The Philosophy of Artificial Intelligence 1990: 248-280
1980 – 1989
- 1989
- [j2]Axel Cleeremans, David Servan-Schreiber, James L. McClelland:
Finite State Automata and Simple Recurrent Networks. Neural Comput. 1(3): 372-381 (1989) - [c4]James L. McClelland:
Connectionist Models of Language. IWPT 1989: 219-220 - 1988
- [c3]David Servan-Schreiber, Axel Cleeremans, James L. McClelland:
Learning Subsequential Structure in Simple Recurrent Networks. NIPS 1988: 643-652 - 1987
- [c2]Geoffrey E. Hinton, James L. McClelland:
Learning Representations by Recirculation. NIPS 1987: 358-366 - [c1]James L. McClelland:
Parallel Distributed Processing and Role Assignment Constraints. TINLAP 1987: 75-79 - 1985
- [j1]James L. McClelland:
Putting Knowledge in its Place: A Scheme for Programming Parallel Processing Structures on the Fly. Cogn. Sci. 9(1): 113-146 (1985)
Coauthor Index
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