Leila Wehbe - RankMe

38 papers A* 14Journal 19Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers. ICLR Andrew F. Luo, Jacob Yeung, Rushikesh Zawar, Shaurya Dewan, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr
2025	J	`jnl`	Estimating Brain Activity with High Spatial and Temporal Resolution using a Naturalistic MEG-fMRI Encoding Model. CoRR Beige Jerry Jin, Leila Wehbe
2025	J	`jnl`	Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex. CoRR Muquan Yu, Mu Nan, Hossein Adeli, Jacob S. Prince, John A. Pyles, Leila Wehbe, Margaret M. Henderson, Michael J. Tarr, Andrew F. Luo
2025	J	`jnl`	Modeling the language cortex with form-independent and enriched representations of sentence meaning reveals remarkable semantic abstractness. CoRR Shreya Saha, Shurui Li, Greta Tuckute, Yuanning Li, Ru-Yuan Zhang, Leila Wehbe, Evelina Fedorenko, Meenakshi Khosla
2024	J	`jnl`	Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers. CoRR Andrew F. Luo, Jacob Yeung, Rushikesh Zawar, Shaurya Dewan, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr
2024	A*	`conf`	BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity. ICLR Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr, Leila Wehbe
2024	A*	`conf`	Divergences between Language Models and Human Brains. NeurIPS Yuchen Zhou, Emmy Liu, Graham Neubig, Michael J. Tarr, Leila Wehbe
2024	J	`jnl`	StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic Images. CoRR Rushikesh Zawar, Shaurya Dewan, Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr, Leila Wehbe
2024	J	`jnl`	Stacked regressions and structured variance partitioning for interpretable brain maps. NeuroImage Ruogu Lin, Thomas Naselaris, Kendrick N. Kay, Leila Wehbe
2023	J	`jnl`	Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset. Nat. Mac. Intell. Aria Y. Wang, Kendrick N. Kay, Thomas Naselaris, Michael J. Tarr, Leila Wehbe
2023	A*	`conf`	Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models. NeurIPS Andrew F. Luo, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr
2023	J	`jnl`	Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models. CoRR Andrew F. Luo, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr
2023	A*	`conf`	Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images. NeurIPS Gabriel Sarch, Michael J. Tarr, Katerina Fragkiadaki, Leila Wehbe
2023	J	`jnl`	BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity. CoRR Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr, Leila Wehbe
2023	J	`jnl`	Divergences between Language Models and Human Brains. CoRR Yuchen Zhou, Emmy Liu, Graham Neubig, Leila Wehbe
2023	A*	`conf`	Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity. NeurIPS Joel Ye, Jennifer L. Collinger, Leila Wehbe, Robert Gaunt
2022	J	`jnl`	Combining computational controls with natural text reveals aspects of meaning composition. Nat. Comput. Sci. Mariya Toneva, Tom M. Mitchell, Leila Wehbe
2022	J	`jnl`	Prospective Learning: Back to the Future. CoRR Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
2022	—	`conf`	Same Cause; Different Effects in the Brain. CLeaR Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe
2022	J	`jnl`	Same Cause; Different Effects in the Brain. CoRR Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe
2021	J	`jnl`	Behavior measures are predicted by how information is encoded in an individual's brain. CoRR Jennifer Williams, Leila Wehbe
2021	A*	`conf`	Can fMRI reveal the representation of syntactic structure in the brain? NeurIPS Aniketh Janardhan Reddy, Leila Wehbe
2021	J	`jnl`	Single-Trial MEG Data Can Be Denoised Through Cross-Subject Predictive Modeling. Frontiers Comput. Neurosci. Srinivas Ravishankar, Mariya Toneva, Leila Wehbe
2020	A*	`conf`	Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction. NeurIPS Mariya Toneva, Otilia Stretcu, Barnabás Póczos, Leila Wehbe, Tom M. Mitchell
2020	J	`jnl`	Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction. CoRR Mariya Toneva, Otilia Stretcu, Barnabás Póczos, Leila Wehbe, Tom M. Mitchell
2019	A*	`conf`	Inducing brain-relevant bias in natural language processing models. NeurIPS Dan Schwartz, Mariya Toneva, Leila Wehbe
2019	J	`jnl`	Inducing brain-relevant bias in natural language processing models. CoRR Dan Schwartz, Mariya Toneva, Leila Wehbe
2019	A*	`conf`	Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain). NeurIPS Mariya Toneva, Leila Wehbe
2019	J	`jnl`	Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain). CoRR Mariya Toneva, Leila Wehbe
2019	A*	`conf`	Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity. NeurIPS Aria Y. Wang, Michael J. Tarr, Leila Wehbe
2019	—	`conf`	Self-Discriminative Learning for Unsupervised Document Embedding. NAACL-HLT (1) Hong-You Chen, Chin-Hua Hu, Leila Wehbe, Shou-De Lin
2016	—	`ed.`	Machine Learning and Interpretation in Neuroimaging - 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers MLINI@NIPS Irina Rish, Georg Langs, Leila Wehbe, Guillermo A. Cecchi, Kai-min Kevin Chang, Brian Murphy
2015	—	`conf`	A Compositional and Interpretable Semantic Space. HLT-NAACL Alona Fyshe, Leila Wehbe, Partha Pratim Talukdar, Brian Murphy, Tom M. Mitchell
2015	A*	`conf`	Nonparametric Independence Testing for Small Sample Sizes. IJCAI Aaditya Ramdas, Leila Wehbe
2015	A*	`conf`	The Spatio-Temporal Representation of Natural Reading. IJCAI Leila Wehbe
2015	—	`—`	The Time and Location of Natural Reading Processes in the Brain. Leila Wehbe
2014	A*	`conf`	Aligning context-based statistical models of language with brain activity during reading. EMNLP Leila Wehbe, Ashish Vaswani, Kevin Knight, Tom M. Mitchell
2012	J	`jnl`	Tracking neural coding of perceptual and semantic features of concrete nouns. NeuroImage Gustavo P. Sudre, Dean Pomerleau, Mark Palatucci, Leila Wehbe, Alona Fyshe, Riitta Salmelin, Tom M. Mitchell