David I. Inouye

54 papers A* 15A 4B 1Journal 29Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FedLOE: Federated Domain Generalization via Locally Overfit Ensemble. Trans. Mach. Learn. Res. Ruqi Bai, David I. Inouye
2025	J	`jnl`	Att-Adapter: A Robust and Precise Domain-Specific Multi-Attributes T2I Diffusion Adapter via Conditional Variational Autoencoder. CoRR Wonwoong Cho, Yan-Ying Chen, Matthew Klenk, David I. Inouye, Yanxia Zhang
2025	A*	`conf`	Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization. ICML Ziyu Gong, Jim Lim, David I. Inouye
2025	J	`jnl`	Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization. CoRR Ziyu Gong, Jim Lim, David I. Inouye
2025	J	`jnl`	From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual Matching. CoRR Ruqi Bai, Yao Ji, Zeyu Zhou, David I. Inouye
2025	J	`jnl`	Imagine for Me: Creative Conceptual Blending of Real Images and Text via Blended Attention. CoRR Wonwoong Cho, Yanxia Zhang, Yan-Ying Chen, David I. Inouye
2025	J	`jnl`	PO-Flow: Flow-based Generative Models for Sampling Potential Outcomes and Counterfactuals. CoRR Dongze Wu, David I. Inouye, Yao Xie
2025	B	`conf`	Robust Collaborative Inference with Vertically Split Data Over Dynamic Device Environments. MobiHoc Surojit Ganguli, Zeyu Zhou, Christopher Brinton, David I. Inouye
2025	J	`jnl`	Your VAR Model is Secretly an Efficient and Explainable Generative Classifier. CoRR Yi-Chung Chen, David I. Inouye, Jing Gao
2024	A*	`conf`	Benchmarking Algorithms for Federated Domain Generalization. ICLR Ruqi Bai, Saurabh Bagchi, David I. Inouye
2024	A*	`conf`	Counterfactual Fairness by Combining Factual and Counterfactual Predictions. NeurIPS Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024	J	`jnl`	Counterfactual Fairness by Combining Factual and Counterfactual Predictions. CoRR Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024	J	`jnl`	Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data. CoRR Avi Amalanshu, Yash Sirvi, David I. Inouye
2024	—	`conf`	Enhanced Controllability of Diffusion Models via Feature Disentanglement and Realism-Enhanced Sampling Methods. ECCV (37) Wonwoong Cho, Hareesh Ravi, Midhun Harikumar, Vinh Khuc, Krishna Kumar Singh, Jingwan Lu, David I. Inouye, Ajinkya Kale
2024	J	`jnl`	StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CoRR Sean Kulinski, Nicholas R. Waytowich, James Zachary Hare, David I. Inouye
2024	A*	`conf`	Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models. ICLR Zeyu Zhou, Ruqi Bai, Sean Kulinski, Murat Kocaoglu, David I. Inouye
2024	A	`conf`	Towards Practical Non-Adversarial Distribution Matching. AISTATS Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye
2024	A	`conf`	Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions. UAI Mai Elkady, Thu Bui, Bruno Ribeiro, David I. Inouye
2024	J	`jnl`	Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions. CoRR Mai Elkady, Thu Bui, Bruno Ribeiro, David I. Inouye
2023	J	`jnl`	Benchmarking Algorithms for Federated Domain Generalization. CoRR Ruqi Bai, Saurabh Bagchi, David I. Inouye
2023	A*	`conf`	Efficient Federated Domain Translation. ICLR Zeyu Zhou, Sheikh Shams Azam, Christopher G. Brinton, David I. Inouye
2023	J	`jnl`	Fault-Tolerant Vertical Federated Learning on Dynamic Networks. CoRR Surojit Ganguli, Zeyu Zhou, Christopher G. Brinton, David I. Inouye
2023	A*	`conf`	StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CVPR Sean Kulinski, Nicholas R. Waytowich, James Zachary Hare, David I. Inouye
2023	J	`jnl`	Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models. CoRR Sean Kulinski, Zeyu Zhou, Ruqi Bai, Murat Kocaoglu, David I. Inouye
2023	J	`jnl`	Towards Enhanced Controllability of Diffusion Models. CoRR Wonwoong Cho, Hareesh Ravi, Midhun Harikumar, Vinh Khuc, Krishna Kumar Singh, Jingwan Lu, David I. Inouye, Ajinkya Kale
2023	A*	`conf`	Towards Explaining Distribution Shifts. ICML Sean Kulinski, David I. Inouye
2023	J	`jnl`	Towards Practical Non-Adversarial Distribution Alignment via Variational Bounds. CoRR Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye
2022	A*	`conf`	Cooperative Distribution Alignment via JSD Upper Bound. NeurIPS Wonwoong Cho, Ziyu Gong, David I. Inouye
2022	J	`jnl`	Cooperative Distribution Alignment via JSD Upper Bound. CoRR Wonwoong Cho, Ziyu Gong, David I. Inouye
2022	A*	`conf`	Discrete Tree Flows via Tree-Structured Permutations. ICML Mai Elkady, Hyung Zin Lim, David I. Inouye
2022	J	`jnl`	Discrete Tree Flows via Tree-Structured Permutations. CoRR Mai Elkady, Jim Lim, David I. Inouye
2022	A	`conf`	Iterative Alignment Flows. AISTATS Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar, David I. Inouye
2022	J	`jnl`	Towards Explaining Distribution Shifts. CoRR Sean Kulinski, David I. Inouye
2022	—	`conf`	Towards Explaining Image-Based Distribution Shifts. CVPR Workshops Sean Kulinski, David I. Inouye
2021	J	`jnl`	Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests. CoRR Sean Kulinski, Saurabh Bagchi, David I. Inouye
2021	J	`jnl`	Iterative Barycenter Flows. CoRR David I. Inouye, Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar
2021	A*	`conf`	Shapley Explanation Networks. ICLR Rui Wang, Xiaoqian Wang, David I. Inouye
2021	J	`jnl`	Shapley Explanation Networks. CoRR Rui Wang, Xiaoqian Wang, David I. Inouye
2020	A	`conf`	Automated Dependence Plots. UAI David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar
2020	J	`jnl`	Enhanced 3DMM Attribute Control via Synthetic Dataset Creation Pipeline. CoRR Wonwoong Cho, Inyeop Lee, David I. Inouye
2020	J	`jnl`	Exploring Adversarial Examples via Invertible Neural Networks. CoRR Ruqi Bai, Saurabh Bagchi, David I. Inouye
2020	A*	`conf`	Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests. NeurIPS Sean Kulinski, Saurabh Bagchi, David I. Inouye
2020	J	`jnl`	Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America. Int. J. Appl. Earth Obs. Geoinformation Donal O'Leary III, David I. Inouye, Ralph Dubayah, Chengquan Huang, George C. Hurtt
2020	J	`jnl`	StyleUV: Diverse and High-fidelity UV Map Generative Model. CoRR Myunggi Lee, Wonwoong Cho, Moonheum Kim, David I. Inouye, Nojun Kwak
2019	J	`jnl`	Diagnostic Curves for Black Box Models. CoRR David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar
2019	J	`jnl`	How Sensitive are Sensitivity-Based Explanations? CoRR Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar
2019	A*	`conf`	On the (In)fidelity and Sensitivity of Explanations. NeurIPS Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar
2018	A*	`conf`	Deep Density Destructors. ICML David I. Inouye, Pradeep Ravikumar
2016	A*	`conf`	Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. ICML David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2015	—	`conf`	Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. NIPS David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2014	A*	`conf`	Admixture of Poisson MRFs: A Topic Model with Word Dependencies. ICML David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. NIPS David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon
2014	J	`jnl`	Summarization of Twitter Microblogs. Comput. J. Beaux Sharifi, David I. Inouye, Jugal K. Kalita
2011	—	`conf`	Comparing Twitter Summarization Algorithms for Multiple Post Summaries. SocialCom/PASSAT David I. Inouye, Jugal K. Kalita