Gong, Chengyue

36 publications

ICLR 2025 Distilling Structural Representations into Protein Sequence Models Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao, Philipp Kraehenbuehl, Adam Klivans, Daniel Jesus Diaz

ICLRW 2025 High-Order Matching for One-Step Shortcut Diffusion Models Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan

UAI 2025 NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Xugang Ye

ICLRW 2025 RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation Yuefan Cao, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song

NeurIPSW 2024 Distilling Structural Representations into Protein Sequence Models Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao, Philipp Kraehenbuehl, Adam Klivans, Daniel Jesus Diaz

ICML 2024 Evolution-Inspired Loss Functions for Protein Representation Learning Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz

ICLRW 2024 Evolution-Inspired Loss Functions for Protein Representation Learning Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz

AAAI 2024 Layer Compression of Deep Networks with Straight Flows Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu

ICML 2024 Switchable Decision: Dynamic Neural Generation Networks Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou

NeurIPSW 2023 Binding Oracle: Fine-Tuning from Stability to Binding Free Energy Chengyue Gong, Adam Klivans, Jordan Wells, James Loy, Qiang Liu, Alex Dimakis, Daniel Diaz

CVPR 2023 Fast Point Cloud Generation with Straight Flows Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu

ICLR 2023 Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu, Chengyue Gong, Qiang Liu

CVPR 2023 FlowGrad: Controlling the Output of Generative ODEs with Gradients Xingchao Liu, Lemeng Wu, Shujian Zhang, Chengyue Gong, Wei Ping, Qiang Liu

ICLR 2023 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew Ellington, Alex Dimakis, Adam Klivans

NeurIPSW 2023 Microenvironment Flows as Protein Engineers Chengyue Gong, Lemeng Wu, Daniel Diaz, Xingchao Liu, James Loy, Adam Klivans, Qiang Liu

NeurIPS 2022 Diffusion-Based Molecule Generation with Informative Prior Bridges Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu

NeurIPSW 2022 Diffusion-Based Molecule Generation with Informative Prior Bridges Chengyue Gong, Lemeng Wu, Xingchao Liu, Mao Ye, Qiang Liu

NeurIPSW 2022 Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu, Chengyue Gong, Qiang Liu

NeurIPSW 2022 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew Ellington, Alex Dimakis, Adam Klivans

ICML 2022 How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity Chengyue Gong, Lemeng Wu, Qiang Liu

ICLR 2022 NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict Aware Supernet Training Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra

CVPR 2021 AlphaMatch: Improving Consistency for Semi-Supervised Learning with Alpha-Divergence Chengyue Gong, Dilin Wang, Qiang Liu

ICML 2021 AlphaNet: Improved Training of Supernets with Alpha-Divergence Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra

NeurIPS 2021 Argmax Centroid Chengyue Gong, Mao Ye, Qiang Liu

CVPR 2021 AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra

NeurIPS 2021 Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach Chengyue Gong, Xingchao Liu, Qiang Liu

CVPR 2021 KeepAugment: A Simple Information-Preserving Data Augmentation Approach Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu

CVPR 2021 MaxUp: Lightweight Adversarial Training with Data Augmentation Improves Neural Network Training Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu

NeurIPS 2020 Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu

ICML 2020 Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu

ICML 2019 Improving Neural Language Modeling via Adversarial Training Dilin Wang, Chengyue Gong, Qiang Liu

ICML 2019 Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization Chengyue Gong, Jian Peng, Qiang Liu

AAAI 2019 Sentence-Wise Smooth Regularization for Sequence to Sequence Learning ChengYue Gong, Xu Tan, Di He, Tao Qin

NeurIPS 2018 FRAGE: Frequency-Agnostic Word Representation Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu

IJCAI 2018 Neural User Response Generator: Fake News Detection with Collective User Intelligence Feng Qian, ChengYue Gong, Karishma Sharma, Yan Liu

NeurIPS 2017 Deep Dynamic Poisson Factorization Model Chengyue Gong, Win-Bin Huang