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ORCIDTie-Yan Liu
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- affiliation: Microsoft Research Asia, Beijing, China
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2020 – today
- 2024
[j72]Shuxin Zheng
, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Predicting equilibrium distributions for molecular systems with deep learning. Nat. Mac. Intell. 6(5): 558-567 (2024)- [j71]Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. Neural Networks 176: 106354 (2024) - [j70]Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Sheng Zhao, Tao Qin, Frank K. Soong, Tie-Yan Liu:
NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4234-4245 (2024) - [j69]Juntao Li, Xiaobo Liang, Lijun Wu, Yue Wang, Qi Meng, Tao Qin, Min Zhang, Tie-Yan Liu:
Randomness Regularization With Simple Consistency Training for Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5763-5778 (2024) - [c303]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. AAAI 2024: 22614-22622 - [c302]Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu:
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation. ICLR 2024 - [c301]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. ICML 2024 - [c300]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction. ICML 2024 - [c299]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen:
Provable Adaptivity of Adam under Non-uniform Smoothness. KDD 2024: 2960-2969 - [i226]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Hamiltonian Prediction. CoRR abs/2403.09560 (2024) - [i225]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR abs/2406.16853 (2024) - 2023
- [j68]Zimeng Li, Shichao Zhu, Bin Shao, Xiangxiang Zeng, Tong Wang, Tie-Yan Liu:
DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning. Briefings Bioinform. 24(1) (2023) - [j67]Jiacheng Lin, Lijun Wu, Jinhua Zhu, Xiaobo Liang, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu:
R2-DDI: relation-aware feature refinement for drug-drug interaction prediction. Briefings Bioinform. 24(1) (2023) - [j66]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131(1): 134-159 (2023) - [j65]Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Incorporating NODE with pre-trained neural differential operator for learning dynamics. Neurocomputing 528: 48-58 (2023) - [j64]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j63]Jinhua Zhu, Yingce Xia, Lijun Wu, Jiajun Deng, Wengang Zhou, Tao Qin, Tie-Yan Liu, Houqiang Li:
Masked Contrastive Representation Learning for Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3421-3433 (2023) - [j62]Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, Tie-Yan Liu:
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11407-11427 (2023) - [j61]Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang:
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c298]Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu:
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations. AAAI 2023: 7740-7747 - [c297]Yichong Leng, Xu Tan, Wenjie Liu, Kaitao Song, Rui Wang, Xiang-Yang Li, Tao Qin, Edward Lin, Tie-Yan Liu:
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition. AAAI 2023: 13034-13042 - [c296]Yisheng Xiao, Ruiyang Xu, Lijun Wu, Juntao Li, Tao Qin, Tie-Yan Liu, Min Zhang:
AMOM: Adaptive Masking over Masking for Conditional Masked Language Model. AAAI 2023: 13789-13797 - [c295]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. ACL (2) 2023: 1606-1616 - [c294]Zixin Zeng, Rui Wang, Yichong Leng, Junliang Guo, Shufang Xie, Xu Tan, Tao Qin, Tie-Yan Liu:
Extract and Attend: Improving Entity Translation in Neural Machine Translation. ACL (Findings) 2023: 1697-1710 - [c293]Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS 2023: 3034-3047 - [c292]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. ICLR 2023 - [c291]Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR 2023 - [c290]Jinhua Zhu, Yue Wang, Lijun Wu, Tao Qin, Wengang Zhou, Tie-Yan Liu, Houqiang Li:
Making Better Decision by Directly Planning in Continuous Control. ICLR 2023 - [c289]Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
𝒪-GNN: incorporating ring priors into molecular modeling. ICLR 2023 - [c288]Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu:
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition. ICML 2023: 13993-14006 - [c287]Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu:
Retrosynthetic Planning with Dual Value Networks. ICML 2023: 22266-22276 - [c286]Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu:
Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. KDD 2023: 506-517 - [c285]Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu:
Web-based Long-term Spine Treatment Outcome Forecasting. KDD 2023: 3082-3092 - [c284]Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu:
Dual-view Molecular Pre-training. KDD 2023: 3615-3627 - [c283]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. KDD 2023: 4003-4012 - [c282]Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan:
FABind: Fast and Accurate Protein-Ligand Binding. NeurIPS 2023 - [c281]Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Geometric Transformer with Interatomic Positional Encoding. NeurIPS 2023 - [i224]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i223]Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu:
Retrosynthetic Planning with Dual Value Networks. CoRR abs/2301.13755 (2023) - [i222]Zijie Geng, Shufang Xie, Yingce Xia, Lijun Wu, Tao Qin, Jie Wang, Yongdong Zhang, Feng Wu, Tie-Yan Liu:
De Novo Molecular Generation via Connection-aware Motif Mining. CoRR abs/2302.01129 (2023) - [i221]Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu:
Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. CoRR abs/2302.05104 (2023) - [i220]Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu:
NeuralStagger: accelerating physics-constrained neural PDE solver with spatial-temporal decomposition. CoRR abs/2302.10255 (2023) - [i219]Zequn Liu, Wei Zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu:
MolXPT: Wrapping Molecules with Text for Generative Pre-training. CoRR abs/2305.10688 (2023) - [i218]Zixin Zeng, Rui Wang, Yichong Leng, Junliang Guo, Xu Tan, Tao Qin, Tie-Yan Liu:
Extract and Attend: Improving Entity Translation in Neural Machine Translation. CoRR abs/2306.02242 (2023) - [i217]Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning. CoRR abs/2306.05445 (2023) - [i216]Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu:
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. CoRR abs/2307.03119 (2023) - [i215]Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan:
FABind: Fast and Accurate Protein-Ligand Binding. CoRR abs/2310.06763 (2023) - 2022
- [j60]Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu, Tong Wang:
Improved drug-target interaction prediction with intermolecular graph transformer. Briefings Bioinform. 23(5) (2022) - [j59]Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu:
BioGPT: generative pre-trained transformer for biomedical text generation and mining. Briefings Bioinform. 23(6) (2022) - [j58]Lijun Wu, Chengcan Yin, Jinhua Zhu, Zhen Wu, Liang He, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu:
SPRoBERTa: protein embedding learning with local fragment modeling. Briefings Bioinform. 23(6) (2022) - [j57]Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Tao Qin, Tie-Yan Liu:
Discovering drug-target interaction knowledge from biomedical literature. Bioinform. 38(22): 5100-5107 (2022) - [j56]Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu:
Stabilize deep ResNet with a sharp scaling factor τ. Mach. Learn. 111(9): 3359-3392 (2022) - [j55]Xiaobo Liang, Lijun Wu, Juntao Li, Tao Qin, Min Zhang, Tie-Yan Liu:
Multi-Teacher Distillation With Single Model for Neural Machine Translation. IEEE ACM Trans. Audio Speech Lang. Process. 30: 992-1002 (2022) - [j54]Bo Yang, Lijun Wu, Jinhua Zhu, Bo Shao, Xiaola Lin, Tie-Yan Liu:
Multimodal Sentiment Analysis With Two-Phase Multi-Task Learning. IEEE ACM Trans. Audio Speech Lang. Process. 30: 2015-2024 (2022) - [j53]Liang He, Bin Shao, Yanghua Xiao, Yatao Li, Tie-Yan Liu, Enhong Chen, Huanhuan Xia:
Neurally-Guided Semantic Navigation in Knowledge Graph. IEEE Trans. Big Data 8(3): 607-615 (2022) - [j52]Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu:
Direct Molecular Conformation Generation. Trans. Mach. Learn. Res. 2022 (2022) - [c280]Chang Liu, Xu Tan, Chongyang Tao, Zhenxin Fu, Dongyan Zhao, Tie-Yan Liu, Rui Yan:
ProphetChat: Enhancing Dialogue Generation with Simulation of Future Conversation. ACL (1) 2022: 962-973 - [c279]Zhuocheng Gong, Di He, Yelong Shen, Tie-Yan Liu, Weizhu Chen, Dongyan Zhao, Ji-Rong Wen, Rui Yan:
Finding the Dominant Winning Ticket in Pre-Trained Language Models. ACL (Findings) 2022: 1459-1472 - [c278]Yi Ren, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Revisiting Over-Smoothness in Text to Speech. ACL (1) 2022: 8197-8213 - [c277]Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff, Tie-Yan Liu:
Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation. CoG 2022: 237-244 - [c276]Zhiping Luo, Wentao Xu, Weiqing Liu, Jiang Bian, Jian Yin, Tie-Yan Liu:
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings. COLING 2022: 2598-2607 - [c275]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR 2022: 15202-15212 - [c274]Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiang-Yang Li, Tao Qin, Tie-Yan Liu:
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method. EMNLP 2022: 5426-5437 - [c273]Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Tie-Yan Liu, Rui Yan:
Target-Side Input Augmentation for Sequence to Sequence Generation. ICLR 2022 - [c272]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. ICLR 2022 - [c271]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. ICLR 2022 - [c270]Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu:
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. ICLR 2022 - [c269]Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu:
Gradient Information Matters in Policy Optimization by Back-propagating through Model. ICLR 2022 - [c268]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu:
SE(3) Equivariant Graph Neural Networks with Complete Local Frames. ICML 2022: 5583-5608 - [c267]Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu:
Supervised Off-Policy Ranking. ICML 2022: 10323-10339 - [c266]Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li:
Analyzing and Mitigating Interference in Neural Architecture Search. ICML 2022: 24646-24662 - [c265]Yihan Wu, Xu Tan, Bohan Li, Lei He, Sheng Zhao, Ruihua Song, Tao Qin, Tie-Yan Liu:
AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. INTERSPEECH 2022: 2568-2572 - [c264]Peiling Lu, Xu Tan, Botao Yu, Tao Qin, Sheng Zhao, Tie-Yan Liu:
MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks. ISMIR 2022: 567-574 - [c263]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Availability Attacks Create Shortcuts. KDD 2022: 2367-2376 - [c262]Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu:
Unified 2D and 3D Pre-Training of Molecular Representations. KDD 2022: 2626-2636 - [c261]Chen Zhang, LuChin Chang, Songruoyao Wu, Xu Tan, Tao Qin, Tie-Yan Liu, Kejun Zhang:
ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships. ACM Multimedia 2022: 1047-1056 - [c260]Kexun Zhang, Rui Wang, Xu Tan, Junliang Guo, Yi Ren, Tao Qin, Tie-Yan Liu:
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation. NAACL-HLT 2022: 1747-1757 - [c259]Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu:
An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. NeurIPS 2022 - [c258]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. NeurIPS 2022 - [c257]Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiangyang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu:
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. NeurIPS 2022 - [c256]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. NeurIPS 2022 - [c255]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. NeurIPS 2022 - [c254]Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS 2022 - [c253]Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu:
Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation. NeurIPS 2022 - [i214]Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Tong Wang, Yusong Wang, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu:
Direct Molecular Conformation Generation. CoRR abs/2202.01356 (2022) - [i213]Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu:
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. CoRR abs/2202.06450 (2022) - [i212]Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu:
Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR abs/2202.09340 (2022) - [i211]Lin Huang, Qiyuan Dong, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
AF2: Adaptive Focus Framework for Aerial Imagery Segmentation. CoRR abs/2202.10322 (2022) - [i210]Lin Huang, Lijun Wu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting. CoRR abs/2202.10586 (2022) - [i209]Yi Ren, Xu Tan, Tao Qin, Zhou Zhao, Tie-Yan Liu:
Revisiting Over-Smoothness in Text to Speech. CoRR abs/2202.13066 (2022) - [i208]Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu:
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR abs/2203.04810 (2022) - [i207]Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu:
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. CoRR abs/2203.07681 (2022) - [i206]Zimeng Li, Shichao Zhu, Bin Shao, Tie-Yan Liu, Xiangxiang Zeng, Tong Wang:
Multi-View Substructure Learning for Drug-Drug Interaction Prediction. CoRR abs/2203.14513 (2022) - [i205]Yihan Wu, Xu Tan, Bohan Li, Lei He, Sheng Zhao, Ruihua Song, Tao Qin, Tie-Yan Liu:
AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios. CoRR abs/2204.00436 (2022) - [i204]Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu:
Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR abs/2204.06255 (2022) - [i203]Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao:
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR abs/2204.06644 (2022) - [i202]Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, Tie-Yan Liu:
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond. CoRR abs/2204.09269 (2022) - [i201]Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, Yuanhao Yi, Lei He, Frank K. Soong, Tao Qin, Sheng Zhao, Tie-Yan Liu:
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality. CoRR abs/2205.04421 (2022) - [i200]Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu:
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. CoRR abs/2205.12418 (2022) - [i199]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. CoRR abs/2205.13401 (2022) - [i198]Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu:
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. CoRR abs/2205.14807 (2022) - [i197]Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang:
Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent. CoRR abs/2206.02617 (2022) - [i196]Wenlei Shi, Xinquan Huang, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu:
LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. CoRR abs/2206.09418 (2022) - [i195]Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu:
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. CoRR abs/2206.09571 (2022) - [i194]Qizhi Pei, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Haiguang Liu