James L. McClelland
- Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
2013/12/20 by Andrew Saxe, Andrew M. Saxe, James L. McClelland +4 · 1 voice · 139 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · #Gaussian Processes and Bayesian Inference #Model Reduction and Neural Networks #Neural Networks and Applications #cond-mat.dis-nn #cs.CV #cs.LG #cs.NE #q-bio.NC #stat.ML
- The TRACE model of speech perception
1986/01/01 by James L McClelland, James L. McClelland, Jeffrey L Elman +1 · 70 citations
Psychology · Neuroscience · #Reading and Literacy Development #Phonetics and Phonology Research #Neurobiology of Language and Bilingualism
- On the control of automatic processes: A parallel distributed processing account of the Stroop effect.
1990/01/01 by Jonathan Cohen, Jonathan D. Cohen, Kevin Dunbar +1 · 25 citations
Neuroscience · #Neural and Behavioral Psychology Studies #EEG and Brain-Computer Interfaces #Visual perception and processing mechanisms
- The time course of perceptual choice: The leaky, competing accumulator model.
2001/01/01 by Marius Usher, James L. McClelland · 29 citations
Neuroscience · Computer Science · #Neural dynamics and brain function #Neural Networks and Applications #Blind Source Separation Techniques
- Hippocampal conjunctive encoding, storage, and recall: Avoiding a trade‐off
1994/12/01 by Randall C. O’Reilly, Randall C. O'Reilly, James L. McClelland · 15 citations
Neuroscience · #Memory and Neural Mechanisms #Neural dynamics and brain function #Neuroscience and Neuropharmacology Research
- SODA: Bottleneck Diffusion Models for Representation Learning
2023/11/29 by Drew A. Hudson, Daniel Zoran, Hudson, Drew A. +15 · 10 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
- On the generalization of language models from in-context learning and finetuning: a controlled study
2025/05/01 by Andrew K. Lampinen, Arslan Chaudhry, Lampinen, Andrew K. +18 · 4 voices · 11 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling #cs.AI #cs.CL #cs.LG
- Distributed memory and the representation of general and specific information.
1985/06/01 by James L. McClelland, David E. Rumelhart · 2 citations
- Environmental drivers of systematicity and generalization in a situated agent
2019/10/01 by Felix Hill, Hill, Felix, Andrew K. Lampinen +11 · 5 citations
Social Sciences · Computer Science · #Language and cultural evolution #Evolutionary Algorithms and Applications #Multi-Agent Systems and Negotiation
- Predicting native English-like performance by native Japanese speakers
2011/05/23 by Erin M. Ingvalson, James L. McClelland, Lori L. Holt · 1 citation
Computer Science · Psychology · Social Sciences · #Linguistic Variation and Morphology #Phonetics and Phonology Research #Speech and dialogue systems
- Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences
2025/09/19 by Andrew Kyle Lampinen, Martin Engelcke, Lampinen, Andrew Kyle +7 · 3 voices · 4 citations
#cs.LG #cs.CL
- Learning the structure of event sequences.
1991/01/01 by Axel Cleeremans, James L. McClelland · 1 citation
Biochemistry, Genetics and Molecular Biology · #Biomedical Text Mining and Ontologies #Machine Learning in Bioinformatics
- Emergent Symbol-like Number Variables in Artificial Neural Networks
2025/01/10 by Satchel Grant, Noah D. Goodman, Grant, Satchel +3 · 2 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG)