A new framework of probabilistic production simulation of power systems with wind energy resources. - Tianyu Ding; Zhaohong Bie; Can Sun; Xiuli Wang; Xifan Wang (ISGT Europe, 2012)

An Analytical Method for Probabilistic Modeling of the Steady-State Behavior of Secondary Residential System. - Tianyu Ding; Hao Liang 002; Wilsun Xu (IEEE Trans. Smart Grid, 2017)

Early Detection of Sepsis Using Ensemblers. - Shailesh Nirgudkar; Tianyu Ding (CinC, 2019)

Noisy Dual Principal Component Pursuit. - Tianyu Ding; Zhihui Zhu; Tianjiao Ding; Yunchen Yang; Daniel P. Robinson; Manolis C. Tsakiris; René Vidal (ICML, 2019)

A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning. - Zhihui Zhu; Tianyu Ding; Daniel P. Robinson; Manolis C. Tsakiris; René Vidal (NeurIPS, 2019)

Orthant Based Proximal Stochastic Gradient Method for ℓ 1-Regularized Optimization. - Tianyi Chen; Tianyu Ding; Bo Ji 003; Guanyi Wang; Yixin Shi; Jing Tian; Sheng Yi; Xiao Tu; Zhihui Zhu (ECML/PKDD (3), 2020)

Orthant Based Proximal Stochastic Gradient Method for 𝓁1-Regularized Optimization. - Tianyi Chen; Tianyu Ding; Bo Ji 003; Guanyi Wang; Yixin Shi; Sheng Yi; Xiao Tu; Zhihui Zhu (CoRR, 2020)

Neural Network Compression Via Sparse Optimization. - Tianyi Chen; Bo Ji 003; Yixin Shi; Tianyu Ding; Biyi Fang; Sheng Yi; Xiao Tu (CoRR, 2020)

Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms. - Tianyu Ding; Zhihui Zhu; Manolis C. Tsakiris; René Vidal; Daniel P. Robinson (AISTATS, 2021)

CDFI: Compression-Driven Network Design for Frame Interpolation. - Tianyu Ding; Luming Liang; Zhihui Zhu; Ilya Zharkov (CVPR, 2021)

Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach. - Tianyu Ding; Zhihui Zhu; René Vidal; Daniel P. Robinson (ICML, 2021)

Only Train Once: A One-Shot Neural Network Training And Pruning Framework. - Tianyi Chen; Bo Ji 003; Tianyu Ding; Biyi Fang; Guanyi Wang; Zhihui Zhu; Luming Liang; Yixin Shi; Sheng Yi; Xiao Tu (NeurIPS, 2021)

A Geometric Analysis of Neural Collapse with Unconstrained Features. - Zhihui Zhu; Tianyu Ding; Jinxin Zhou; Xiao Li 026; Chong You; Jeremias Sulam; Qing Qu 001 (NeurIPS, 2021)

SAGCN: Towards Structure-Aware Deep Graph Convolutional Networks on Node Classification. - Ming He 001; Tianyu Ding; Tianshuo Han (PAKDD (2), 2021)

RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution. - Zhicheng Geng; Luming Liang; Tianyu Ding; Ilya Zharkov (CVPR, 2022)

Learning and Fusing Multiple User Interest Representations for Sequential Recommendation. - Ming He 001; Tianshuo Han; Tianyu Ding (DASFAA (3), 2022)

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. - Jinxin Zhou; Xiao Li 026; Tianyu Ding; Chong You; Qing Qu 001; Zhihui Zhu (ICML, 2022)

Multilevel Feature Interaction Learning for Session-Based Recommendation via Graph Neural Networks. - Ming He 001; Tianshuo Han; Tianyu Ding (ICWE, 2022)

Sparsity-guided Network Design for Frame Interpolation. - Tianyu Ding; Luming Liang; Zhihui Zhu; Tianyi Chen; Ilya Zharkov (CoRR, 2022)

OTOv2: Automatic, Generic, User-Friendly. - Tianyi Chen; Luming Liang; Tianyu Ding; Zhihui Zhu; Ilya Zharkov (ICLR, 2023)

Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs. - Yanqi Bao; Yuxin Li; Jing Huo; Tianyu Ding; Xinyue Liang; Wenbin Li 006; Yang Gao 001 (ACM Multimedia, 2023)

Efficient Subgame Refinement for Extensive-form Games. - Zhenxing Ge; Zheng Xu; Tianyu Ding; Wenbin Li 006; Yang Gao 001 (NeurIPS, 2023)

Towards Automatic Neural Architecture Search within General Super-Networks. - Tianyi Chen; Luming Liang; Tianyu Ding; Ilya Zharkov (CoRR, 2023)

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery. - Tianyi Chen; Tianyu Ding; Badal Yadav; Ilya Zharkov; Luming Liang (CoRR, 2023)

The Efficiency Spectrum of Large Language Models: An Algorithmic Survey. - Tianyu Ding; Tianyi Chen; Haidong Zhu; Jiachen Jiang; Yiqi Zhong; Jinxin Zhou; Guangzhi Wang; Zhihui Zhu; Ilya Zharkov; Luming Liang (CoRR, 2023)

OTOv3: Automatic Architecture-Agnostic Neural Network Training and Compression from Structured Pruning to Erasing Operators. - Tianyi Chen; Tianyu Ding; Zhihui Zhu; Zeyu Chen; HsiangTao Wu; Ilya Zharkov; Luming Liang (CoRR, 2023)

Conversation and recommendation: knowledge-enhanced personalized dialog system. - Ming He 001; Jiwen Wang; Tianyu Ding; Tong Shen (Knowl. Inf. Syst., 2023)

Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation. - Wenxiao Deng; Wenbin Li 006; Tianyu Ding; Lei Wang 001; Hongguang Zhang; Kuihua Huang; Jing Huo; Yang Gao 001 (CVPR, 2024)

DREAM: Diffusion Rectification and Estimation-Adaptive Models. - Jinxin Zhou; Tianyu Ding; Tianyi Chen; Jiachen Jiang; Ilya Zharkov; Zhihui Zhu; Luming Liang (CVPR, 2024)

CaesarNeRF: Calibrated Semantic Representation for Few-Shot Generalizable Neural Rendering. - Haidong Zhu; Tianyu Ding; Tianyi Chen; Ilya Zharkov; Ram Nevatia; Luming Liang (ECCV (6), 2024)

InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules. - Yanqi Bao; Tianyu Ding; Jing Huo; Wenbin Li 006; Yuxin Li; Yang Gao 001 (ICLR, 2024)

Safe and Robust Subgame Exploitation in Imperfect Information Games. - Zhenxing Ge; Zheng Xu; Tianyu Ding; Linjian Meng; Bo An 001; Wenbin Li 006; Yang Gao 001 (ICML, 2024)

Re-examining Supervised Dimension Reduction for High-Dimensional Bayesian Optimization. - Quanlin Chen; Jing Huo; Yiyu Chen; Tianyu Ding; Yang Gao 001; Dong Li 016; Xu He (PPSN (2), 2024)

Task-Aware Few-Shot Image Generation via Dynamic Local Distribution Estimation and Sampling. - Zheng Gu 001; Wenbin Li 006; Tianyu Ding; Zhengli Wang; Jing Huo; Kuihua Huang; Yang Gao 001 (PRCV (2), 2024)

S3Editor: A Sparse Semantic-Disentangled Self-Training Framework for Face Video Editing. - Guangzhi Wang; Tianyi Chen; Kamran Ghasedi; HsiangTao Wu; Tianyu Ding; Chris Nuesmeyer; Ilya Zharkov; Mohan S. Kankanhalli; Luming Liang (CoRR, 2024)

AdaContour: Adaptive Contour Descriptor with Hierarchical Representation. - Tianyu Ding; Jinxin Zhou; Tianyi Chen; Zhihui Zhu; Ilya Zharkov; Luming Liang (CoRR, 2024)

FORA: Fast-Forward Caching in Diffusion Transformer Acceleration. - Pratheba Selvaraju; Tianyu Ding; Tianyi Chen; Ilya Zharkov; Luming Liang (CoRR, 2024)

Probing the Robustness of Vision-Language Pretrained Models: A Multimodal Adversarial Attack Approach. - Jiwei Guan; Tianyu Ding; Longbing Cao; Lei Pan 002; Chen Wang 008; Xi Zheng 001 (CoRR, 2024)

VERA: Validation and Evaluation of Retrieval-Augmented Systems. - Tianyu Ding; Adi Banerjee; Laurent Mombaerts; Yunhong Li; Tarik Borogovac; Juan Pablo De la Cruz Weinstein (CoRR, 2024)

HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning. - Tianyi Chen; Xiaoyi Qu; David Aponte; Colby R. Banbury; Jongwoo Ko; Tianyu Ding; Yong Ma; Vladimir Lyapunov; Ilya Zharkov; Luming Liang (CoRR, 2024)

Analyzing and Improving Model Collapse in Rectified Flow Models. - Huminhao Zhu; Fangyikang Wang; Tianyu Ding; Qing Qu 001; Zhihui Zhu (CoRR, 2024)

StructSR: Refuse Spurious Details in Real-World Image Super-Resolution. - Yachao Li; Dong Liang 008; Tianyu Ding; Sheng-Jun Huang (AAAI, 2025)

CoT-VTM: Visual-to-Music Generation with Chain-of-Thought Reasoning. - Xikang Guan; Zheng Gu 001; Jing Huo; Tianyu Ding; Yang Gao 001 (ACL (Findings), 2025)

Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality Calibration. - Yiyang Chen; Tianyu Ding; Lei Wang 001; Jing Huo; Yang Gao 001; Wenbin Li 006 (CVPR, 2025)

Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression. - Xiaoyi Qu; David Aponte; Colby R. Banbury; Daniel P. Robinson; Tianyu Ding; Kazuhito Koishida; Ilya Zharkov; Tianyi Chen (CVPR, 2025)

OFER: Occluded Face Expression Reconstruction. - Pratheba Selvaraju; Victoria Fernández Abrevaya; Timo Bolkart; Rick Akkerman; Tianyu Ding; Faezeh Amjadi; Ilya Zharkov (CVPR, 2025)

DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs. - Jongwoo Ko; Tianyi Chen; Sungnyun Kim; Tianyu Ding; Luming Liang; Ilya Zharkov; Se-Young Yun (CoRR, 2025)

Robust Dataset Distillation by Matching Adversarial Trajectories. - Wei Lai; Tianyu Ding; Dongdong Ren; Lei Wang 001; Jing Huo; Yang Gao 001; Wenbin Li 006 (CoRR, 2025)

Cat-AIR: Content and Task-Aware All-in-One Image Restoration. - Jiachen Jiang; Tianyu Ding; Ke Zhang; Jinxin Zhou; Tianyi Chen; Ilya Zharkov; Zhihui Zhu; Luming Liang (CoRR, 2025)

ProCrop: Learning Aesthetic Image Cropping from Professional Compositions. - Ke Zhang; Tianyu Ding; Jiachen Jiang; Tianyi Chen; Ilya Zharkov; Vishal M. Patel; Luming Liang (CoRR, 2025)

ONNXPruner: ONNX-Based General Model Pruning Adapter. - Dongdong Ren; Wenbin Li 006; Tianyu Ding; Lei Wang 001; Qi Fan; Jing Huo; Hongbing Pan; Yang Gao 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities. - Yanqi Bao; Tianyu Ding; Jing Huo; Yaoli Liu; Yuxin Li; Wenbin Li 006; Yang Gao 001; Jiebo Luo 001 (IEEE Trans. Circuits Syst. Video Technol., 2025)

Multi-Task Multi-Agent Reinforcement Learning With Interaction and Task Representations. - Chao Li; Shaokang Dong; Shangdong Yang; Yujing Hu; Tianyu Ding; Wenbin Li 006; Yang Gao 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

State Abstraction via Deep Supervised Hash Learning. - Guang Yang; Zheng Xu; Jing Huo; Shangdong Yang; Tianyu Ding; Xingguo Chen; Yang Gao 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Robust unsupervised visual tracking via image-to-video identity knowledge transferring. - Bin Kang; Zongyu Wang; Dong Liang 008; Tianyu Ding; Songlin Du (Pattern Recognit., 2026)