Pipeline image haze removal system using dark channel prior on cloud processing platform. - Ce Li; Tan He; Yingheng Wang; Liguo Zhang; Ruili Liu; Jing Zheng (Int. J. Comput. Sci. Eng., 2020)

MolCloze: A Unified Cloze-style Self-supervised Molecular Structure Learning Model for Chemical Property Prediction. - Yingheng Wang; Xin Chen; Yaosen Min; Ji Wu 002 (BIBM, 2021)

Molecular Graph Contrastive Learning with Parameterized Explainable Augmentations. - Yingheng Wang; Yaosen Min; Erzhuo Shao; Ji Wu 002 (BIBM, 2021)

One-shot Transfer Learning for Population Mapping. - Erzhuo Shao; Jie Feng 002; Yingheng Wang; Tong Xia; Yong Li 008 (CIKM, 2021)

Multi-view Graph Contrastive Representation Learning for Drug-Drug Interaction Prediction. - Yingheng Wang; Yaosen Min; Xin Chen; Ji Wu 002 (WWW, 2021)

Going Deeper into Permutation-Sensitive Graph Neural Networks. - Zhongyu Huang; Yingheng Wang; Chaozhuo Li; Huiguang He (ICML, 2022)

Graph Emotion Decoding from Visually Evoked Neural Responses. - Zhongyu Huang; Changde Du; Yingheng Wang; Huiguang He (MICCAI (8), 2022)

Predicting the protein-ligand affinity from molecular dynamics trajectories. - Yaosen Min; Ye Wei; Peizhuo Wang; Nian Wu; Stefan Bauer; Shuxin Zheng; Yu Shi; Yingheng Wang; Dan Zhao 004; Ji Wu 002; Jianyang Zeng 001 (CoRR, 2022)

Time Series Contrastive Learning with Information-Aware Augmentations. - Dongsheng Luo; Wei Cheng 002; Yingheng Wang; Dongkuan Xu; Jingchao Ni; Wenchao Yu; Xuchao Zhang; Yanchi Liu; Yuncong Chen; Haifeng Chen; Xiang Zhang 001 (AAAI, 2023)

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models. - Yingheng Wang; Yair Schiff; Aaron Gokaslan; Weishen Pan; Fei Wang 001; Christopher De Sa; Volodymyr Kuleshov (ICML, 2023)

M2Hub: Unlocking the Potential of Machine Learning for Materials Discovery. - Yuanqi Du; Yingheng Wang; Yining Huang; Jianan Canal Li; Yanqiao Zhu 001; Tian Xie; Chenru Duan; John M. Gregoire; Carla Pedro Gomes (NeurIPS, 2023)

Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction. - Junwen Bai; Yuanqi Du; Yingheng Wang; Shufeng Kong; John M. Gregoire; Carla Gomes 001 (CoRR, 2023)

ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers. - Junjie Yin; Jiahao Dong; Yingheng Wang; Christopher De Sa; Volodymyr Kuleshov (CoRR, 2023)

Graph Data Augmentation for Graph Machine Learning: A Survey. - Tong Zhao 003; Wei Jin 009; Yozen Liu; Yingheng Wang; Gang Liu 025; Stephan Günnemann; Neil Shah; Meng Jiang 001 (IEEE Data Eng. Bull., 2023)

Graph-Enhanced Emotion Neural Decoding. - Zhongyu Huang; Changde Du; Yingheng Wang; Kaicheng Fu; Huiguang He (IEEE Trans. Medical Imaging, 2023)

Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance. - Yingheng Wang; Shufeng Kong; John M. Gregoire; Carla P. Gomes (AAAI, 2024)

GEM-RAG: Graphical Eigen Memories for Retrieval Augmented Generation. - Brendan Hogan Rappazzo; Yingheng Wang; Aaron M. Ferber; Carla Gomes 001 (ICMLA, 2024)

Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors. - Top Piriyakulkij; Yingheng Wang; Volodymyr Kuleshov (CoRR, 2024)

Long-context Protein Language Model. - Yingheng Wang; Zichen Wang 002; Gil Sadeh; Luca Zancato; Alessandro Achille; George Karypis; Huzefa Rangwala (CoRR, 2024)

Machine learning-aided generative molecular design. - Yuanqi Du; Arian R. Jamasb; Jeff Guo; Tianfan Fu; Charles Harris; Yingheng Wang; Chenru Duan; Pietro Liò; Philippe Schwaller; Tom L. Blundell (Nat. Mac. Intell., 2024)

ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers. - Junjie Yin; Jiahao Dong; Yingheng Wang; Christopher De Sa; Volodymyr Kuleshov (Trans. Mach. Learn. Res., 2024)

Growing Like a Tree: Finding Trunks From Graph Skeleton Trees. - Zhongyu Huang; Yingheng Wang; Chaozhuo Li; Huiguang He (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors. - Wasu Top Piriyakulkij; Yingheng Wang; Volodymyr Kuleshov (AAAI, 2025)

LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers. - Yingheng Wang; Zichen Wang 002; Gil Sadeh; Luca Zancato; Alessandro Achille; George Karypis; Huzefa Rangwala (Trans. Mach. Learn. Res., 2025)

Graffe: Graph Representation Learning via Diffusion Probabilistic Models. - Dingshuo Chen; Shuchen Xue; Liuji Chen; Yingheng Wang; Qiang Liu; Shu Wu; Zhi-Ming Ma; Liang Wang (CoRR, 2025)

MTCMB: A Multi-Task Benchmark Framework for Evaluating LLMs on Knowledge, Reasoning, and Safety in Traditional Chinese Medicine. - Shufeng Kong; Xingru Yang; Yuanyuan Wei 011; Zijie Wang; Hao Tang; Jiuqi Qin; Shuting Lan; Yingheng Wang; Junwen Bai; Zhuangbin Chen; Zibin Zheng; Caihua Liu; et al. (CoRR, 2025)

HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization. - Hongzheng Chen; Yingheng Wang; Yaohui Cai; Hins Hu; Jiajie Li; Shirley Huang; Chenhui Deng; Rongjian Liang; Shufeng Kong; Haoxing Ren; Samitha Samaranayake; Carla P. Gomes; et al. (CoRR, 2025)

Improving Multislice Electron Ptychography with a Generative Prior. - Christian K. Belardi; Chia-Hao Lee; Yingheng Wang; Justin Lovelace; Kilian Q. Weinberger; David A. Muller; Carla P. Gomes (CoRR, 2025)