Leila Wehbe
Leila Wehbe
Verified email at cmu.edu - Homepage
Cited by
Cited by
Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses
L Wehbe, B Murphy, P Talukdar, A Fyshe, A Ramdas, T Mitchell
PloS one 9 (11), e112575, 2014
Tracking neural coding of perceptual and semantic features of concrete nouns
G Sudre, D Pomerleau, M Palatucci, L Wehbe, A Fyshe, R Salmelin, ...
NeuroImage 62 (1), 451-463, 2012
Aligning context-based statistical models of language with brain activity during reading
L Wehbe, A Vaswani, K Knight, T Mitchell
Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
M Toneva, L Wehbe
arXiv preprint arXiv:1905.11833, 2019
A compositional and interpretable semantic space
A Fyshe, L Wehbe, P Talukdar, B Murphy, T Mitchell
Proceedings of the 2015 conference of the north american chapter of the …, 2015
Inducing brain-relevant bias in natural language processing models
D Schwartz, M Toneva, L Wehbe
arXiv preprint arXiv:1911.03268, 2019
The lexical semantics of adjective–noun phrases in the human brain
A Fyshe, G Sudre, L Wehbe, N Rafidi, TM Mitchell
Human brain mapping 40 (15), 4457-4469, 2019
Regularized brain reading with shrinkage and smoothing
L Wehbe, A Ramdas, RC Steorts, CR Shalizi
The Annals of Applied Statistics 9 (4), 1997-2022, 2015
Nonparametric independence testing for small sample sizes
A Ramdas, L Wehbe
24th International Conference on Artificial Intelligence, 3777-3783, 2015
Incremental language comprehension difficulty predicts activity in the language network but not the multiple demand network
L Wehbe, IA Blank, C Shain, R Futrell, R Levy, T von der Malsburg, ...
Cerebral Cortex 31 (9), 4006-4023, 2021
Neural taskonomy: Inferring the similarity of task-derived representations from brain activity
AY Wang, L Wehbe, M Tarr
Decoding language from the brain
B Murphy, L Wehbe, A Fyshe
Language, cognition, and computational models, 53-80, 2018
Can fMRI reveal the representation of syntactic structure in the brain?
AJ Reddy, L Wehbe
Advances in Neural Information Processing Systems 34, 2021
Combining computational controls with natural text reveals new aspects of meaning composition
M Toneva, TM Mitchell, L Wehbe
bioRxiv, 2020
Self-Discriminative Learning for Unsupervised Document Embedding
HY Chen, CH Hu, L Wehbe, SD Lin
Proceedings of the 2019 Conference of the North American Chapter of the …, 2019
Decoding word semantics from magnetoencephalography time series transformations
A Fyshe, G Sudre, L Wehbe, B Murphy, T Mitchell
Proceedings of the 3rd Workshop on Machine Learning and Inference in …, 2012
A Deep Learning Model for Automated Classification of Intraoperative Continuous EMG
X Zha, L Wehbe, RJ Sclabassi, Z Mace, YV Liang, A Yu, J Leonardo, ...
IEEE Transactions on Medical Robotics and Bionics 3 (1), 44-52, 2020
The Time and Location of Natural Reading Processes in the Brain
L Wehbe
Ph. D. Dissertation, 2015
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
M Toneva, O Stretcu, B Póczos, L Wehbe, TM Mitchell
Advances in Neural Information Processing Systems 33, 2020
Single-trial MEG data can be denoised through cross-subject predictive modeling
S Ravishankar, M Toneva, L Wehbe
Frontiers in computational neuroscience, 82, 2021
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