Action Representation and Purpose: Re-evaluating the Foundations of Computational Vision. - Michael J. Black; Yiannis Aloimonos; Christopher M. Brown; Ian Horswill; Jitendra Malik; Giulio Sandini; Michael J. Tarr (IJCAI, 1993)

Representation of three-dimensional object similarity in human vision. - Florin Cutzu; Michael J. Tarr (Human Vision and Electronic Imaging, 1997)

Inferring Perceptual Saliency Fields from Viewpoint-Dependent Recognition Data. - Florin Cutzu; Michael J. Tarr (Neural Comput., 1999)

Quantitative Comparative Evaluation of 2D Vector Field Visualization Methods. - David H. Laidlaw; Robert M. Kirby; J. Scott Davidson; Timothy S. Miller; Marco da Silva; William H. Warren; Michael J. Tarr (IEEE Visualization, 2001)

Early lateralization and orientation tuning for face, word, and object processing in the visual cortex. - Bruno Rossion; Carrie A. Joyce; Garrison W. Cottrell; Michael J. Tarr (NeuroImage, 2003)

Behavioral Change and Its Neural Correlates in Visual Agnosia After Expertise Training. - Marlene Behrmann; Jonathan J. Marotta; Isabel Gauthier; Michael J. Tarr; Thomas J. McKeeff (J. Cogn. Neurosci., 2005)

Comparing 2D Vector Field Visualization Methods: A User Study. - David H. Laidlaw; Robert M. Kirby; Cullen D. Jackson; J. Scott Davidson; Timothy S. Miller; Marco da Silva; William H. Warren; Michael J. Tarr (IEEE Trans. Vis. Comput. Graph., 2005)

Perceptual Expertise Effects Are Not All or None: Spatially Limited Perceptual Expertise for Faces in a Case of Prosopagnosia. - Cindy M. Bukach; Daniel N. Bub; Isabel Gauthier; Michael J. Tarr (J. Cogn. Neurosci., 2006)

Is Region-of-Interest Overlap Comparison a Reliable Measure of Category Specificity? - Chun-Chia Kung; Jessie J. Peissig; Michael J. Tarr (J. Cogn. Neurosci., 2007)

Identifying faces across variations in lighting: Psychophysics and computation. - Michael J. Tarr; Athinodoros S. Georghiades; Cullen D. Jackson (ACM Trans. Appl. Percept., 2008)

Race-Specific Perceptual Discrimination Improvement Following Short Individuation Training With Faces. - Rankin W. McGugin; James W. Tanaka; Sophie Lebrecht; Michael J. Tarr; Isabel Gauthier (Cogn. Sci., 2011)

Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization. - Ying Yang; Michael J. Tarr; Robert E. Kass (MLINI@NIPS, 2014)

Exploration of complex visual feature spaces for object perception. - Daniel D. Leeds; John A. Pyles; Michael J. Tarr (Frontiers Comput. Neurosci., 2014)

Applying artificial vision models to human scene understanding. - Elissa Michele Aminoff; Mariya Toneva; Abhinav Shrivastava; Xinlei Chen; Ishan Misra; Abhinav Gupta 001; Michael J. Tarr (Frontiers Comput. Neurosci., 2015)

Size Precedes View: Developmental Emergence of Invariant Object Representations in Lateral Occipital Complex. - Mayu Nishimura; K. Suzanne Scherf; Valentinos Zachariou; Michael J. Tarr; Marlene Behrmann (J. Cogn. Neurosci., 2015)

Containing errors in computations for neural sensing: Does a hierarchical-referencing strategy lead to energy savings? - Matthew Boring; Shawn K. Kelly; Jeffrey A. Weldon; Michael J. Tarr; Amanda Robinson 001; Marlene Behrmann; Pulkit Grover (ITA, 2016)

A state-space model of cross-region dynamic connectivity in MEG/EEG. - Ying Yang; Elissa Aminoff; Michael J. Tarr; Robert E. Kass (NIPS, 2016)

A method for real-time visual stimulus selection in the study of cortical object perception. - Daniel D. Leeds; Michael J. Tarr (NeuroImage, 2016)

Functionally localized representations contain distributed information: insight from simulations of deep convolutional neural networks. - Nicholas Blauch; Elissa Aminoff; Michael J. Tarr (CogSci, 2017)

Challenges and Opportunities in Instrumentation and Use of High-Density EEG for Underserved Regions. - Ashwati Krishnan; Ritesh Kumar; Arnelle Etienne; Amanda K. Robinson; Shawn K. Kelly; Marlene Behrmann; Michael J. Tarr; Pulkit Grover (InterSol, 2018)

BOLD5000: A public fMRI dataset of 5000 images. - Nadine Chang; John A. Pyles; Abhinav Gupta 001; Michael J. Tarr; Elissa M. Aminoff (CoRR, 2018)

Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity. - Aria Y. Wang; Michael J. Tarr; Leila Wehbe (NeurIPS, 2019)

Learning Intermediate Features of Object Affordances with a Convolutional Neural Network. - Aria Yuan Wang; Michael J. Tarr (CoRR, 2020)

Alpha Net: Adaptation with Composition in Classifier Space. - Nadine Chang; Jayanth Koushik; Michael J. Tarr; Martial Hebert; Yu-Xiong Wang (CoRR, 2020)

TIDEE: Tidying Up Novel Rooms Using Visuo-Semantic Commonsense Priors. - Gabriel Sarch; Zhaoyuan Fang; Adam W. Harley; Paul Schydlo; Michael J. Tarr; Saurabh Gupta 001; Katerina Fragkiadaki (ECCV (39), 2022)

Learning Neural Acoustic Fields. - Andrew F. Luo; Yilun Du; Michael J. Tarr; Josh Tenenbaum 001; Antonio Torralba 001; Chuang Gan 001 (NeurIPS, 2022)

Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models. - Gabriel Sarch; Yue Wu; Michael J. Tarr; Katerina Fragkiadaki (EMNLP (Findings), 2023)

Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models. - Andrew F. Luo; Margaret M. Henderson; Leila Wehbe; Michael J. Tarr (NeurIPS, 2023)

Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images. - Gabriel Sarch; Michael J. Tarr; Katerina Fragkiadaki; Leila Wehbe (NeurIPS, 2023)

Quantifying the Roles of Visual, Linguistic, and Visual-Linguistic Complexity in Verb Acquisition. - Yuchen Zhou 004; Michael J. Tarr; Daniel Yurovsky (CoRR, 2023)

Thinking Like an Annotator: Generation of Dataset Labeling Instructions. - Nadine Chang; Francesco Ferroni; Michael J. Tarr; Martial Hebert; Deva Ramanan (CoRR, 2023)

3D View Prediction Models of the Dorsal Visual Stream. - Gabriel Sarch; Hsiao-Yu Fish Tung; Aria Y. Wang; Jacob S. Prince; Michael J. Tarr (CoRR, 2023)

Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset. - Aria Y. Wang; Kendrick N. Kay; Thomas Naselaris; Michael J. Tarr; Leila Wehbe (Nat. Mac. Intell., 2023)

BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity. - Andrew F. Luo; Margaret M. Henderson; Michael J. Tarr; Leila Wehbe (ICLR, 2024)

VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought. - Gabriel Sarch; Lawrence Jang; Michael J. Tarr; William W. Cohen; Kenneth Marino; Katerina Fragkiadaki (NeurIPS, 2024)

Divergences between Language Models and Human Brains. - Yuchen Zhou 004; Emmy Liu; Graham Neubig; Michael J. Tarr; Leila Wehbe (NeurIPS, 2024)

HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models. - Gabriel Sarch; Sahil Somani; Raghav Kapoor; Michael J. Tarr; Katerina Fragkiadaki (CoRR, 2024)

Neural Representations of Dynamic Visual Stimuli. - Jacob Yeung; Andrew F. Luo; Gabriel Sarch; Margaret M. Henderson; Deva Ramanan; Michael J. Tarr (CoRR, 2024)

StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic Images. - Rushikesh Zawar; Shaurya Dewan; Andrew F. Luo; Margaret M. Henderson; Michael J. Tarr; Leila Wehbe (CoRR, 2024)

ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights. - Gabriel Sarch; Lawrence Jang; Michael J. Tarr; William W. Cohen; Kenneth Marino; Katerina Fragkiadaki (CoRR, 2024)

Reanimating Images using Neural Representations of Dynamic Stimuli. - Jacob Yeung; Andrew F. Luo; Gabriel Sarch; Margaret M. Henderson; Deva Ramanan; Michael J. Tarr (CVPR, 2025)

Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers. - Andrew F. Luo; Jacob Yeung; Rushikesh Zawar; Shaurya Dewan; Margaret M. Henderson; Leila Wehbe; Michael J. Tarr (ICLR, 2025)

Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex. - Muquan Yu; Mu Nan; Hossein Adeli; Jacob S. Prince; John A. Pyles; Leila Wehbe; Margaret M. Henderson; Michael J. Tarr; Andrew F. Luo (CoRR, 2025)

Grounded Reinforcement Learning for Visual Reasoning. - Gabriel Sarch; Snigdha Saha; Naitik Khandelwal; Ayush Jain; Michael J. Tarr; Aviral Kumar; Katerina Fragkiadaki (CoRR, 2025)