Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions? - Aditi Jha; Sumeet Agarwal (CogSci, 2019)

Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction. - Aditi Jha; Michael J. Morais; Jonathan W. Pillow (ICML, 2021)

Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior. - Zoe Ashwood; Aditi Jha; Jonathan W. Pillow (NeurIPS, 2022)

Bayesian Active Learning for Discrete Latent Variable Models. - Aditi Jha; Zoe C. Ashwood; Jonathan W. Pillow (CoRR, 2022)

LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms. - Aditi Jha; Sam Havens; Jeremy Dohmann; Alex Trott; Jacob P. Portes (CoRR, 2023)

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks. - Aditi Jha; Joshua C. Peterson; Thomas L. Griffiths 001 (Cogn. Sci., 2023)

Multi Task Learning for Predicting Music Video Clip and Participant Identification from Brain Responses. - Jhanvi H. Mehta; Muskan Priyadarshani; Aditi Jha; Krishna P. Miyapuram (COMAD/CODS (December), 2024)

Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems. - Aditi Jha; Diksha Gupta; Carlos D. Brody; Jonathan W. Pillow (NeurIPS, 2024)

Active Learning for Discrete Latent Variable Models. - Aditi Jha; Zoe C. Ashwood; Jonathan W. Pillow (Neural Comput., 2024)

"Heptadecanol" a phytochemical multi-target inhibitor of SMYD3 & GFPT2 proteins in non-small cell lung cancer: an in-silico & in-vitro investigation. - Lokesh Ravi; Pratishtha Jain; Ajith Kumar K; Jeevan Kumar M; Mukti Panda; Harshitha S; Mohammed Abdul Kareem; K. Sivani Yelchuri Sai; Ayman Fathima; V. Jensha; Adarsh Anurag Rai; Hida Amal Faizal; et al. (J. Comput. Aided Mol. Des., 2025)