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ORCIDDavid I. Inouye
Person information
- affiliation: Purdue University, USA
- affiliation (Ph.D): University of Texas at Austin, Department of Computer Science
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Journal Articles
- 2020
[j2]Donal O'Leary III, David I. Inouye, Ralph Dubayah, Chengquan Huang, George C. Hurtt
:
Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America. Int. J. Appl. Earth Obs. Geoinformation 89: 102110 (2020)- 2014
- [j1]Beaux Sharifi, David I. Inouye, Jugal K. Kalita:
Summarization of Twitter Microblogs. Comput. J. 57(3): 378-402 (2014)
Conference and Workshop Papers
- 2023
- [c17]Sean Kulinski, Nicholas R. Waytowich, James Z. Hare, David I. Inouye:
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CVPR 2023: 22004-22013 - [c16]Zeyu Zhou, Sheikh Shams Azam, Christopher G. Brinton, David I. Inouye:
Efficient Federated Domain Translation. ICLR 2023 - [c15]Sean Kulinski, David I. Inouye:
Towards Explaining Distribution Shifts. ICML 2023: 17931-17952 - 2022
- [c14]Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar, David I. Inouye:
Iterative Alignment Flows. AISTATS 2022: 6409-6444 - [c13]Sean Kulinski, David I. Inouye:
Towards Explaining Image-Based Distribution Shifts. CVPR Workshops 2022: 4787-4791 - [c12]Mai Elkady, Hyung Zin Lim, David I. Inouye:
Discrete Tree Flows via Tree-Structured Permutations. ICML 2022: 5892-5923 - [c11]Wonwoong Cho, Ziyu Gong, David I. Inouye:
Cooperative Distribution Alignment via JSD Upper Bound. NeurIPS 2022 - 2021
- [c10]Rui Wang, Xiaoqian Wang, David I. Inouye:
Shapley Explanation Networks. ICLR 2021 - 2020
- [c9]Sean Kulinski, Saurabh Bagchi, David I. Inouye:
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests. NeurIPS 2020 - [c8]David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar:
Automated Dependence Plots. UAI 2020: 1238-1247 - 2019
- [c7]Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar:
On the (In)fidelity and Sensitivity of Explanations. NeurIPS 2019: 10965-10976 - 2018
- [c6]David I. Inouye, Pradeep Ravikumar:
Deep Density Destructors. ICML 2018: 2172-2180 - 2016
- [c5]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. ICML 2016: 2445-2453 - 2015
- [c4]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial. NIPS 2015: 3213-3221 - 2014
- [c3]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Admixture of Poisson MRFs: A Topic Model with Word Dependencies. ICML 2014: 683-691 - [c2]David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon:
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs. NIPS 2014: 3158-3166 - 2011
- [c1]David I. Inouye, Jugal K. Kalita:
Comparing Twitter Summarization Algorithms for Multiple Post Summaries. SocialCom/PASSAT 2011: 298-306
Informal and Other Publications
- 2024
- [i18]Sean Kulinski, Nicholas R. Waytowich, James Z. Hare, David I. Inouye:
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments. CoRR abs/2401.04290 (2024) - [i17]Avi Amalanshu, Yash Sirvi, David I. Inouye:
Decoupled Vertical Federated Learning for Practical Training on Vertically Partitioned Data. CoRR abs/2403.03871 (2024) - 2023
- [i16]Wonwoong Cho, Hareesh Ravi, Midhun Harikumar, Vinh Khuc, Krishna Kumar Singh, Jingwan Lu, David I. Inouye, Ajinkya Kale:
Towards Enhanced Controllability of Diffusion Models. CoRR abs/2302.14368 (2023) - [i15]Sean Kulinski, Zeyu Zhou, Ruqi Bai, Murat Kocaoglu, David I. Inouye:
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models. CoRR abs/2306.11281 (2023) - [i14]Ruqi Bai, Saurabh Bagchi, David I. Inouye:
Benchmarking Algorithms for Federated Domain Generalization. CoRR abs/2307.04942 (2023) - [i13]Ziyu Gong, Ben Usman, Han Zhao, David I. Inouye:
Towards Practical Non-Adversarial Distribution Alignment via Variational Bounds. CoRR abs/2310.19690 (2023) - [i12]Surojit Ganguli, Zeyu Zhou, Christopher G. Brinton, David I. Inouye:
Fault-Tolerant Vertical Federated Learning on Dynamic Networks. CoRR abs/2312.16638 (2023) - 2022
- [i11]Mai Elkady, Jim Lim, David I. Inouye:
Discrete Tree Flows via Tree-Structured Permutations. CoRR abs/2207.01744 (2022) - [i10]Wonwoong Cho, Ziyu Gong, David I. Inouye:
Cooperative Distribution Alignment via JSD Upper Bound. CoRR abs/2207.02286 (2022) - [i9]Sean Kulinski, David I. Inouye:
Towards Explaining Distribution Shifts. CoRR abs/2210.10275 (2022) - 2021
- [i8]Rui Wang, Xiaoqian Wang, David I. Inouye:
Shapley Explanation Networks. CoRR abs/2104.02297 (2021) - [i7]David I. Inouye, Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar:
Iterative Barycenter Flows. CoRR abs/2104.07232 (2021) - [i6]Sean Kulinski, Saurabh Bagchi, David I. Inouye:
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests. CoRR abs/2107.06929 (2021) - 2020
- [i5]Wonwoong Cho, Inyeop Lee, David I. Inouye:
Enhanced 3DMM Attribute Control via Synthetic Dataset Creation Pipeline. CoRR abs/2011.12833 (2020) - [i4]Myunggi Lee, Wonwoong Cho, Moonheum Kim, David I. Inouye, Nojun Kwak:
StyleUV: Diverse and High-fidelity UV Map Generative Model. CoRR abs/2011.12893 (2020) - [i3]Ruqi Bai, Saurabh Bagchi, David I. Inouye:
Exploring Adversarial Examples via Invertible Neural Networks. CoRR abs/2012.13111 (2020) - 2019
- [i2]Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar:
How Sensitive are Sensitivity-Based Explanations? CoRR abs/1901.09392 (2019) - [i1]David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar:
Diagnostic Curves for Black Box Models. CoRR abs/1912.01108 (2019)
Coauthor Index
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