| 2025 | CVPR | Reanimating Images using Neural Representations of Dynamic Stimuli. | Jacob Yeung, Andrew F. Luo, Gabriel Sarch, Margaret M. Henderson, Deva Ramanan, Michael J. Tarr |
| 2025 | ICLR | 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 |
| 2024 | ICLR | BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity. | Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr, Leila Wehbe |
| 2023 | EMNLP | Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models. | Gabriel Sarch, Yue Wu, Michael J. Tarr, Katerina Fragkiadaki |
| 2022 | ECCV | TIDEE: Tidying Up Novel Rooms Using Visuo-Semantic Commonsense Priors. | Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley, Paul Schydlo, Michael J. Tarr, Saurabh Gupta, Katerina Fragkiadaki |
| 2017 | CogSci | Functionally localized representations contain distributed information: insight from simulations of deep convolutional neural networks. | Nicholas Blauch, Elissa Aminoff, Michael J. Tarr |
| 2016 | ITA | 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, Marlene Behrmann, Pulkit Grover |
| 1993 | IJCAI | 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 |