Follow
Lauren A Phillips
Lauren A Phillips
Unknown affiliation
No verified email
Title
Cited by
Cited by
Year
Few-Shot Learning with Metric-Agnostic Conditional Embeddings
N Hilliard, L Phillips, S Howland, A Yankov, CD Corley, NO Hodas
arXiv preprint arXiv:1802.04376, 2018
1872018
Using social media to predict the future: a systematic literature review
L Phillips, C Dowling, K Shaffer, N Hodas, S Volkova
arXiv preprint arXiv:1706.06134, 2017
902017
The utility of cognitive plausibility in language acquisition modeling: Evidence from word segmentation
L Phillips, L Pearl
Cognitive science 39 (8), 1824-1854, 2015
402015
Metric-Based Few-Shot Learning for Video Action Recognition
C Careaga, B Hutchinson, N Hodas, L Phillips
arXiv preprint arXiv:1909.09602, 2019
322019
Perceptual adaptation to sinewave-vocoded speech across languages.
T Bent, JL Loebach, L Phillips, DB Pisoni
Journal of Experimental Psychology: Human perception and performance 37 (5 …, 2011
222011
Predicting foreign language usage from english-only social media posts
S Volkova, S Ranshous, L Phillips
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
162018
Bayesian inference as a viable cross-linguistic word segmentation strategy: It’s all about what’s useful
L Phillips, L Pearl
Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014
162014
Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things
L Phillips, L Pearl
Proceedings of the 5th Workshop on Cognitive Aspects of Computational …, 2014
162014
Proposal-based few-shot sound event detection for speech and environmental sounds with perceivers
P Wolters, C Daw, B Hutchinson, L Phillips
arXiv preprint arXiv:2107.13616, 2021
152021
Less is more in Bayesian word segmentation: When cognitively plausible learners outperform the ideal
L Phillips, L Pearl
Proceedings of the Annual Meeting of the Cognitive Science Society 34 (34), 2012
142012
Less is more in Bayesian word segmentation: When cognitively plausible learners outperform the ideal
L Phillips, L Pearl
Proceedings of the Annual Meeting of the Cognitive Science Society 34 (34), 2012
142012
Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation
L Phillips, L Pearl
Proceedings of the 6th workshop on cognitive modeling and computational …, 2015
112015
A study of few-shot audio classification
P Wolters, C Careaga, B Hutchinson, L Phillips
arXiv preprint arXiv:2012.01573, 2020
92020
Evaluating language acquisition models: A utility-based look at Bayesian segmentation
L Pearl, L Phillips
Language, cognition, and computational models, 185-224, 2018
62018
Explanatory Masks for Neural Network Interpretability
L Phillips, G Goh, N Hodas
arXiv preprint arXiv:1911.06876, 2019
52019
Fuzzy simplicial networks: A topology-inspired model to improve task generalization in few-shot learning
H Kvinge, Z New, N Courts, JH Lee, LA Phillips, CD Corley, A Tuor, ...
AAAI Workshop on Meta-Learning and MetaDL Challenge, 77-89, 2021
32021
Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks
L Phillips, N Hodas
arXiv preprint arXiv:1706.01839, 2017
32017
The role of empirical evidence in modeling speech segmentation
L Phillips
University of California, Irvine, 2015
22015
Evaluating language acquisition strategies: A cross-linguistic look at early segmentation
L Phillips, L Pearl
Ms., UC Irvine, 2015
22015
Recursive Decoding: A Situated Cognition Approach to Compositional Generation in Grounded Language Understanding
M Setzler, S Howland, L Phillips
arXiv preprint arXiv:2201.11766, 2022
12022
The system can't perform the operation now. Try again later.
Articles 1–20