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Timothy Gentner
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2020 – today
- 2021
- [j4]Tim Sainburg, Leland McInnes, Timothy Q. Gentner:
Parametric UMAP Embeddings for Representation and Semisupervised Learning. Neural Comput. 33(11): 2881-2907 (2021) - [j3]Daril E. Brown II
, Jairo I. Chavez, Derek H. Nguyen
Local field potentials in a pre-motor region predict learned vocal sequences. PLoS Comput. Biol. 17(9) (2021) - [c2]Tim Sainburg, Anna Mai, Timothy Gentner:
Long-range sequential dependencies precede complex syntactic production in language acquisition. CogSci 2021 - 2020
- [j2]Tim Sainburg
Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires. PLoS Comput. Biol. 16(10) (2020) - [j1]Willem H. Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg, Timothy Gentner:
Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning. Top. Cogn. Sci. 12(3): 925-941 (2020) - [i2]Tim Sainburg, Leland McInnes, Timothy Q. Gentner:
Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning. CoRR abs/2009.12981 (2020)
2010 – 2019
- 2019
- [c1]Tim Sainburg, Marvin Thielk, Timothy Gentner:
Animal Vocalization Generative Network (AVGN): A method for visualizing, understanding, and sampling from animal communicative repertoires. CogSci 2019: 3563 - 2018
- [i1]Tim Sainburg
Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions. CoRR abs/1807.06650 (2018)
Coauthor Index
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