First-passage time distribution for random walks on complex networks using inverse Laplace transform and mean-field approximation. - Mucong Ding; Kwok Yip Szeto (CoRR, 2018)

Transfer Learning using Representation Learning in Massive Open Online Courses. - Mucong Ding; Yanbang Wang; Erik Hemberg; Una-May O'Reilly (LAK, 2019)

Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses. - Mucong Ding; Kai Yang; Dit-Yan Yeung; Ting-Chuen Pong (LAK, 2019)

Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs. - Mucong Ding; Constantinos Daskalakis; Soheil Feizi (CoRR, 2020)

FLAG: Adversarial Data Augmentation for Graph Neural Networks. - Kezhi Kong; Guohao Li 001; Mucong Ding; Zuxuan Wu; Chen Zhu 001; Bernard Ghanem; Gavin Taylor; Tom Goldstein (CoRR, 2020)

GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences. - Mucong Ding; Constantinos Daskalakis; Soheil Feizi (AISTATS, 2021)

Understanding Over-parameterization in Generative Adversarial Networks. - Yogesh Balaji; Mohammadmahdi Sajedi; Neha Mukund Kalibhat; Mucong Ding; Dominik Stöger; Mahdi Soltanolkotabi; Soheil Feizi (ICLR, 2021)

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. - Mucong Ding; Kezhi Kong; Jingling Li; Chen Zhu 001; John Dickerson 001; Furong Huang; Tom Goldstein (NeurIPS, 2021)

Understanding Overparameterization in Generative Adversarial Networks. - Yogesh Balaji; Mohammadmahdi Sajedi; Neha Mukund Kalibhat; Mucong Ding; Dominik Stöger; Mahdi Soltanolkotabi; Soheil Feizi (CoRR, 2021)

Robust Optimization as Data Augmentation for Large-scale Graphs. - Kezhi Kong; Guohao Li 001; Mucong Ding; Zuxuan Wu; Chen Zhu 001; Bernard Ghanem; Gavin Taylor; Tom Goldstein (CVPR, 2022)

Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. - Bang An 001; Zora Che; Mucong Ding; Furong Huang (NeurIPS, 2022)

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. - Mucong Ding; Tahseen Rabbani; Bang An 001; Evan Wang; Furong Huang (NeurIPS, 2022)

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation. - Mucong Ding; Bang An 001; Yuancheng Xu; Anirudh Satheesh; Furong Huang (ICLR, 2024)

WAVES: Benchmarking the Robustness of Image Watermarks. - Bang An 001; Mucong Ding; Tahseen Rabbani; Aakriti Agrawal; Yuancheng Xu; Chenghao Deng; Sicheng Zhu; Abdirisak Mohamed; Yuxin Wen; Tom Goldstein; Furong Huang (ICML, 2024)

Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. - Mucong Ding; Chenghao Deng; Jocelyn Choo; Zichu Wu; Aakriti Agrawal; Avi Schwarzschild; Tianyi Zhou 001; Tom Goldstein; John Langford 001; Animashree Anandkumar; Furong Huang (NeurIPS, 2024)

Benchmarking the Robustness of Image Watermarks. - Bang An 001; Mucong Ding; Tahseen Rabbani; Aakriti Agrawal; Yuancheng Xu; Chenghao Deng; Sicheng Zhu; Abdirisak Mohamed; Yuxin Wen; Tom Goldstein; Furong Huang (CoRR, 2024)

Spectral Greedy Coresets for Graph Neural Networks. - Mucong Ding; Yinhan He; Jundong Li; Furong Huang (CoRR, 2024)

Calibrated Dataset Condensation for Faster Hyperparameter Search. - Mucong Ding; Yuancheng Xu; Tahseen Rabbani; Xiaoyu Liu 003; Brian J. Gravelle; Teresa M. Ranadive; Tai-Ching Tuan; Furong Huang (CoRR, 2024)

SAIL: Self-Improving Efficient Online Alignment of Large Language Models. - Mucong Ding; Souradip Chakraborty; Vibhu Agrawal; Zora Che; Alec Koppel; Mengdi Wang; Amrit S. Bedi; Furong Huang (CoRR, 2024)

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. - Mucong Ding; Tahseen Rabbani; Bang An 001; Evan Z. Wang; Furong Huang (CoRR, 2024)

EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM? - Aakriti Agrawal; Mucong Ding; Zora Che; Chenghao Deng; Anirudh Satheesh; John Langford 001; Furong Huang (CoRR, 2024)

PICore: Physics-Informed Unsupervised Coreset Selection for Data Efficient Neural Operator Training. - Anirudh Satheesh; Anant Khandelwal; Mucong Ding; Radu Balan (CoRR, 2025)