Nitesh V Chawla, FACM, FAAAI, FIEEE
University of Notre Dame
H-index: 79
North America-United States
Top articles of Nitesh V Chawla, FACM, FAAAI, FIEEE
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
TinyLLM: Learning a Small Student from Multiple Large Language Models | arXiv preprint arXiv:2402.04616 | Yijun Tian Yikun Han Xiusi Chen Wei Wang Nitesh V Chawla | 2024/2/7 |
Towards a holistic view of bias in machine learning: bridging algorithmic fairness and imbalanced learning | arXiv preprint arXiv:2207.06084 | Damien Dablain Bartosz Krawczyk Nitesh Chawla | 2022/7/13 |
Can we soft prompt LLMs for graph learning tasks? | arXiv preprint arXiv:2402.10359 | Zheyuan Liu Xiaoxin He Yijun Tian Nitesh V Chawla | 2024/2/15 |
Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective | Yihong Ma Xiaobao Huang Bozhao Nan Nuno Moniz Xiangliang Zhang | 2024/2/6 | |
Corrigendum: A community focused approach toward making healthy and affordable daily diet recommendations | Frontiers in big Data | Joe Germino Annalisa Szymanski Heather A Eicher-Miller Ronald Metoyer Nitesh V Chawla | 2024/4/4 |
Node Duplication Improves Cold-start Link Prediction | arXiv preprint arXiv:2402.09711 | Zhichun Guo Tong Zhao Yozen Liu Kaiwen Dong William Shiao | 2024/2/15 |
Large language model based multi-agents: A survey of progress and challenges | Taicheng Guo Xiuying Chen Yaqi Wang Ruidi Chang Shichao Pei | 2024/1/21 | |
Graph neural prompting with large language models | Proceedings of the AAAI Conference on Artificial Intelligence | Yijun Tian Huan Song Zichen Wang Haozhu Wang Ziqing Hu | 2024/3/24 |
UGMAE: A Unified Framework for Graph Masked Autoencoders | arXiv preprint arXiv:2402.08023 | Yijun Tian Chuxu Zhang Ziyi Kou Zheyuan Liu Xiangliang Zhang | 2024/2/12 |
CORE: Data Augmentation for Link Prediction via Information Bottleneck | arXiv preprint arXiv:2404.11032 | Kaiwen Dong Zhichun Guo Nitesh V Chawla | 2024/4/17 |
Understanding imbalanced data: XAI & interpretable ML framework | Machine Learning | Damien Dablain Colin Bellinger Bartosz Krawczyk David W Aha Nitesh Chawla | 2024/1/16 |
Conformalized Selective Regression | arXiv preprint arXiv:2402.16300 | Anna Sokol Nuno Moniz Nitesh Chawla | 2024/2/26 |
Universal link predictor by In-context Learning | arXiv preprint arXiv:2402.07738 | Kaiwen Dong Haitao Mao Zhichun Guo Nitesh V Chawla | 2024/2/12 |
You do not have to train Graph Neural Networks at all on text-attributed graphs | arXiv preprint arXiv:2404.11019 | Kaiwen Dong Zhichun Guo Nitesh V Chawla | 2024/4/17 |
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding | arXiv preprint arXiv:2402.14391 | Lirong Wu Yijun Tian Yufei Huang Siyuan Li Haitao Lin | 2024/2/22 |
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering | arXiv preprint arXiv:2402.07630 | Xiaoxin He Yijun Tian Yifei Sun Nitesh V Chawla Thomas Laurent | 2024/2/12 |
A Property-Guided Diffusion Model For Generating Molecular Graphs | Changsheng Ma Taicheng Guo Qiang Yang Xiuying Chen Xin Gao | 2024/4/14 | |
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns | arXiv preprint arXiv:2403.08820 | Zheyuan Zhang Zehong Wang Shifu Hou Evan Hall Landon Bachman | 2024/2/21 |
Knowledge distillation on graphs: A survey | arXiv preprint arXiv:2302.00219 | Yijun Tian Shichao Pei Xiangliang Zhang Chuxu Zhang Nitesh V Chawla | 2023/2/1 |
Environment and shipping drive environmental DNA beta‐diversity among commercial ports | Molecular Ecology | Jose Andrés Paul Czechowski Erin Grey Mandana Saebi Kara Andres | 2023/12 |
Co-Authors
