Jay McClelland

13 papers B 11Journal 2

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Extending a Mathematical Theory of the Emergence of Knowledge from the Experience to Capture Learning Dynamics in Transformers. CogSci Sabrina Jones, Jay McClelland
2025	B	`conf`	Humans learn proactively in ways that language models don't. CogSci Simon Jerome Han, Jay McClelland
2024	B	`conf`	Symbolic Variables in Distributed Networks that Count. CogSci Satchel Grant, Zhengxuan Wu, Jay McClelland, Noah D. Goodman
2022	J	`jnl`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill
2021	B	`conf`	Are people still smarter than machines? If so, why? CogSci Jay McClelland
2020	B	`conf`	A computational model of learning to count in a multimodal, interactive environment. CogSci Silvester Sabathiel, Jay McClelland, Trygve Solstad
2020	B	`conf`	Cognitive consequences of structured education in a connectionist model of analogical reasoning. CogSci David Barrett, Felix Hill, Adam Santoro, Jay McClelland
2020	B	`conf`	Human-like learning Framework for frequency-skewed multi-level classification. CogSci Amarjot Singh, Jay McClelland
2019	B	`conf`	Modeling Number Sense Acquisition in A Number Board Game by Coordinating Verbal, Visual, and Grounded Action Components. CogSci Arianna Yuan, Jay McClelland
2019	B	`conf`	Symposium in Memory of Jeff Elman: Language Learning, Prediction, and Temporal Dynamics. CogSci Jay McClelland, Ken McRae
2018	B	`conf`	Can Generic Neural Networks Estimate Numerosity Like Humans? CogSci Sharon Chen, Zhenglong Zhou, Mengting Fang, Jay McClelland
2018	B	`conf`	Can a Recurrent Neural Network Learn to Count Things? CogSci Mengting Fang, Zhenglong Zhou, Sharon Chen, Jay McClelland
2010	J	`jnl`	Cognitive Science Meets Autonomous Mental Development. Cogn. Sci. Jay McClelland, Juyang Weng, Gedeon O. Deák, Brian Scassellati