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Mucong Ding

9 papers · 2021–2024 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (21) 👑 Triple Crown

Venues

NeurIPS (4) ICLR (2) AISTATS (1) CVPR (1) ICML (1)

Top co-authors

Furong Huang (6) Bang An (4) Tom Goldstein (4) Tahseen Rabbani (2) Aakriti Agrawal (2) Chen Zhu (2) Soheil Feizi (2) Kezhi Kong (2) Yuancheng Xu (2) Chenghao Deng (2)

Research topics

Machine Learning (8) Deep Learning (5) Learning Types · Machine Learning (5) Optimization & Theory (5) Application Areas (4) Architectures (4) Artificial Intelligence (2) Core AI (2) Natural Language Processing (1) Learning Types · Deep Learning (1) Models (1) Resources & Methods (1) Techniques (1)

Keywords

graph neural network (3) node classification (3) link prediction (2) data augmentation (2) generative adversarial network (2) graph classification (1) robustness (1) few-shot learning (1) subpopulation shift (1) global convergence (1) minimax optimization (1) message passing (1) vector quantization (1) gradient descent (1) domain adaptation (1) markov random field (1) sublinear complexity (1) bilevel optimization (1) bayesian network (1) distribution shift (1)

Papers

Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization NeurIPS 2024 SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation ICLR 2024 WAVES: Benchmarking the Robustness of Image Watermarks ICML 2024 Robust Optimization As Data Augmentation for Large-Scale Graphs CVPR 2022 Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity NeurIPS 2022 Transferring Fairness under Distribution Shifts via Fair Consistency Regularization NeurIPS 2022 GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences AISTATS 2021 Understanding Over-parameterization in Generative Adversarial Networks ICLR 2021 VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization NeurIPS 2021