3D Convolutional Neural Networks for Classification of Functional Connectomes. - Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (DLMIA/ML-CDS@MICCAI, 2018)

Ensemble learning with 3D convolutional neural networks for connectome-based prediction. - Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (CoRR, 2018)

Machine learning in resting-state fMRI analysis. - Meenakshi Khosla; Keith Jamison; Gia H. Ngo; Amy Kuceyeski; Mert R. Sabuncu (CoRR, 2018)

Detecting Abnormalities in Resting-State Dynamics: An Unsupervised Learning Approach. - Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (MLMI@MICCAI, 2019)

Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction. - Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (NeuroImage, 2019)

A Shared Neural Encoding Model for the Prediction of Subject-Specific fMRI Response. - Meenakshi Khosla; Gia H. Ngo; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (MICCAI (7), 2020)

From Connectomic to Task-Evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-State Functional Connectivity. - Gia H. Ngo; Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (MICCAI (7), 2020)

Neural encoding with visual attention. - Meenakshi Khosla; Gia H. Ngo; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (NeurIPS, 2020)

NeuroGen: activation optimized image synthesis for discovery neuroscience. - Zijin Gu; Keith Jamison; Meenakshi Khosla; Emily J. Allen; Yihan Wu; Thomas Naselaris; Kendrick N. Kay; Mert R. Sabuncu; Amy Kuceyeski (CoRR, 2021)

Characterizing the Ventral Visual Stream with Response-Optimized Neural Encoding Models. - Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (NeurIPS, 2022)

NeuroGen: Activation optimized image synthesis for discovery neuroscience. - Zijin Gu; Keith Jamison; Meenakshi Khosla; Emily J. Allen; Yihan Wu; Ghislain St-Yves; Thomas Naselaris; Kendrick N. Kay; Mert R. Sabuncu; Amy Kuceyeski (NeuroImage, 2022)

Predicting individual task contrasts from resting-state functional connectivity using a surface-based convolutional network. - Gia H. Ngo; Meenakshi Khosla; Keith Jamison; Amy Kuceyeski; Mert R. Sabuncu (NeuroImage, 2022)

Soft Matching Distance: A metric on neural representations that captures single-neuron tuning. - Meenakshi Khosla; Alex H. Williams (UniReps, 2023)

Modeling the Human Visual System: Comparative Insights from Response-Optimized and Task-Optimized Vision Models, Language Models, and different Readout Mechanisms. - Shreya Saha; Ishaan Chadha; Meenakshi Khosla (CoRR, 2024)

Evaluating Representational Similarity Measures from the Lens of Functional Correspondence. - Yiqing Bo; Ansh Soni; Sudhanshu Srivastava; Meenakshi Khosla (CoRR, 2024)

Sparse components distinguish visual pathways & their alignment to neural networks. - Ammar I Marvi; Nancy Kanwisher; Meenakshi Khosla (ICLR, 2025)

Brain-Model Evaluations Need the NeuroAI Turing Test. - Jenelle Feather; Meenakshi Khosla; N. Apurva Ratan Murty; Aran Nayebi (CoRR, 2025)

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts. - Chaitanya Kapoor; Sudhanshu Srivastava; Meenakshi Khosla (CoRR, 2025)