| A comparative study of transformer-based language models on extractive question answering K Pearce, T Zhan, A Komanduri, J Zhan arXiv preprint arXiv:2110.03142, 2021 | 32* | 2021 |
| Scm-vae: Learning identifiable causal representations via structural knowledge A Komanduri, Y Wu, W Huang, F Chen, X Wu 2022 IEEE International Conference on Big Data (Big Data), 1014-1023, 2022 | 6 | 2022 |
| From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling A Komanduri, X Wu, Y Wu, F Chen Transactions on Machine Learning Research, 2024 | 4 | 2024 |
| Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms A Komanduri, Y Wu, F Chen, X Wu Proceedings of the 33rd International Joint Conference on Artificial …, 2024 | 3 | 2024 |
| Neighborhood random walk graph sampling for regularized Bayesian graph convolutional neural networks A Komanduri, J Zhan 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 3 | 2021 |
| Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models A Komanduri, C Zhao, F Chen, X Wu arXiv preprint arXiv:2404.17735, 2024 | | 2024 |
Xintao WuUniversity of ArkansasEmail verificata su uark.edu
