Comparing Twitter Summarization Algorithms for Multiple Post Summaries. - David I. Inouye; Jugal K. Kalita (SocialCom/PASSAT, 2011)

Admixture of Poisson MRFs: A Topic Model with Word Dependencies. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2014)

Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Summarization of Twitter Microblogs. - Beaux Sharifi; David I. Inouye; Jugal K. Kalita (Comput. J., 2014)

Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. - David I. Inouye; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Deep Density Destructors. - David I. Inouye; Pradeep Ravikumar (ICML, 2018)

On the (In)fidelity and Sensitivity of Explanations. - Chih-Kuan Yeh; Cheng-Yu Hsieh; Arun Sai Suggala; David I. Inouye; Pradeep Ravikumar (NeurIPS, 2019)

How Sensitive are Sensitivity-Based Explanations? - Chih-Kuan Yeh; Cheng-Yu Hsieh; Arun Sai Suggala; David I. Inouye; Pradeep Ravikumar (CoRR, 2019)

Diagnostic Curves for Black Box Models. - David I. Inouye; Liu Leqi; Joon Sik Kim; Bryon Aragam; Pradeep Ravikumar (CoRR, 2019)

Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests. - Sean Kulinski; Saurabh Bagchi; David I. Inouye (NeurIPS, 2020)

Automated Dependence Plots. - David I. Inouye; Liu Leqi; Joon Sik Kim; Bryon Aragam; Pradeep Ravikumar (UAI, 2020)

Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America. - Donal O'Leary III; David I. Inouye; Ralph Dubayah; Chengquan Huang; George C. Hurtt (Int. J. Appl. Earth Obs. Geoinformation, 2020)

Enhanced 3DMM Attribute Control via Synthetic Dataset Creation Pipeline. - Wonwoong Cho; Inyeop Lee; David I. Inouye (CoRR, 2020)

StyleUV: Diverse and High-fidelity UV Map Generative Model. - Myunggi Lee; Wonwoong Cho; Moonheum Kim; David I. Inouye; Nojun Kwak (CoRR, 2020)

Exploring Adversarial Examples via Invertible Neural Networks. - Ruqi Bai; Saurabh Bagchi; David I. Inouye (CoRR, 2020)

Shapley Explanation Networks. - Rui Wang; Xiaoqian Wang 001; David I. Inouye (ICLR, 2021)

Iterative Barycenter Flows. - David I. Inouye; Zeyu Zhou; Ziyu Gong; Pradeep Ravikumar (CoRR, 2021)

Iterative Alignment Flows. - Zeyu Zhou; Ziyu Gong; Pradeep Ravikumar; David I. Inouye (AISTATS, 2022)

Towards Explaining Image-Based Distribution Shifts. - Sean Kulinski; David I. Inouye (CVPR Workshops, 2022)

Discrete Tree Flows via Tree-Structured Permutations. - Mai Elkady; Hyung Zin Lim; David I. Inouye (ICML, 2022)

Cooperative Distribution Alignment via JSD Upper Bound. - Wonwoong Cho; Ziyu Gong; David I. Inouye (NeurIPS, 2022)

Discrete Tree Flows via Tree-Structured Permutations. - Mai Elkady; Jim Lim; David I. Inouye (CoRR, 2022)

StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. - Sean Kulinski; Nicholas R. Waytowich; James Zachary Hare; David I. Inouye (CVPR, 2023)

Efficient Federated Domain Translation. - Zeyu Zhou; Sheikh Shams Azam; Christopher G. Brinton; David I. Inouye (ICLR, 2023)

Towards Explaining Distribution Shifts. - Sean Kulinski; David I. Inouye (ICML, 2023)

Towards Enhanced Controllability of Diffusion Models. - Wonwoong Cho; Hareesh Ravi; Midhun Harikumar; Vinh Khuc; Krishna Kumar Singh; Jingwan Lu; David I. Inouye; Ajinkya Kale (CoRR, 2023)

Towards Practical Non-Adversarial Distribution Alignment via Variational Bounds. - Ziyu Gong; Ben Usman; Han Zhao 002; David I. Inouye (CoRR, 2023)

Fault-Tolerant Vertical Federated Learning on Dynamic Networks. - Surojit Ganguli; Zeyu Zhou; Christopher G. Brinton; David I. Inouye (CoRR, 2023)

Towards Practical Non-Adversarial Distribution Matching. - Ziyu Gong; Ben Usman; Han Zhao 002; David I. Inouye (AISTATS, 2024)

Enhanced Controllability of Diffusion Models via Feature Disentanglement and Realism-Enhanced Sampling Methods. - Wonwoong Cho; Hareesh Ravi; Midhun Harikumar; Vinh Khuc; Krishna Kumar Singh; Jingwan Lu; David I. Inouye; Ajinkya Kale (ECCV (37), 2024)

Benchmarking Algorithms for Federated Domain Generalization. - Ruqi Bai; Saurabh Bagchi; David I. Inouye (ICLR, 2024)

Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models. - Zeyu Zhou; Ruqi Bai; Sean Kulinski; Murat Kocaoglu; David I. Inouye (ICLR, 2024)

Counterfactual Fairness by Combining Factual and Counterfactual Predictions. - Zeyu Zhou; Tianci Liu 003; Ruqi Bai; Jing Gao 004; Murat Kocaoglu; David I. Inouye (NeurIPS, 2024)

Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions. - Mai Elkady; Thu Bui; Bruno Ribeiro 001; David I. Inouye (UAI, 2024)

Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data. - Avi Amalanshu; Yash Sirvi; David I. Inouye (CoRR, 2024)

Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder. - Wonwoong Cho; Yan-Ying Chen; Matthew Klenk 001; David I. Inouye; Yanxia Zhang (CoRR, 2025)

PO-Flow: Flow-based Generative Models for Sampling Potential Outcomes and Counterfactuals. - Dongze Wu; David I. Inouye; Yao Xie (CoRR, 2025)

From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual Matching. - Ruqi Bai; Yao Ji; Zeyu Zhou; David I. Inouye (CoRR, 2025)

Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization. - Ziyu Gong; Jim Lim; David I. Inouye (CoRR, 2025)

Imagine for Me: Creative Conceptual Blending of Real Images and Text via Blended Attention. - Wonwoong Cho; Yanxia Zhang; Yan-Ying Chen; David I. Inouye (CoRR, 2025)