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ORCIDJian Peng 0001
Person information
- affiliation: HeliXon, Beijing, China
- affiliation (former): University of Illinois at Urbana-Champaign, Department of Computer Science, IL, USA
- affiliation (former): Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
- affiliation (former): Toyota Technological Institute at Chicago, IL, USA
Other persons with the same name
- Jian Peng — disambiguation page
- Jian Peng 0002 — Sichuan University, School of Computer Science (and 1 more)
- Jian Peng 0003
![[0000-0003-0104-522X]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0104-522X")
— Hunan University, College of Mechanical and Vehicle Engineering, China - Jian Peng 0004 — Southeast Missouri State University, Department of Physics and Engineering Physics (and 1 more)
- Jian Peng 0005 — University of Ulster, Ulster Business School
- Jian Peng 0006 — University of Oxford, School of Geography and the Environment, UK (and 2 more)
- Jian Peng 0007 — Peking University, College of Urban and Environmental Sciences, Beijing, China
- Jian Peng 0008 — Hunan University, College of Electrical and Information Engineering, Changsha, China
- Jian Peng 0009 — Central South University, School of Geosciences and Info-Physics, Changsha, China
- Jian Peng 0010 — Hunan University, School of Business Administration, Changsha, China (and 1 more)
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Journal Articles
- 2023
[j23]Yunan Luo, Yang Liu, Jian Peng:
Calibrated geometric deep learning improves kinase-drug binding predictions. Nat. Mac. Intell. 5(12): 1390-1401 (2023)- 2022
- [j22]Jian Peng:
RECOMB 2021 Special Issue. J. Comput. Biol. 29(1): 2 (2022) - [j21]Jian Peng:
RECOMB 2021 Special Issue. J. Comput. Biol. 29(2): 91 (2022) - 2021
- [j20]Alexander P. Wu, Jian Peng, Bonnie Berger, Hyunghoon Cho:
Bayesian information sharing enhances detection of regulatory associations in rare cell types. Bioinform. 37(Supplement): 349-357 (2021) - [j19]Xianggen Liu, Yunan Luo, Pengyong Li, Sen Song, Jian Peng:
Deep geometric representations for modeling effects of mutations on protein-protein binding affinity. PLoS Comput. Biol. 17(8) (2021) - 2020
- [j18]Yunan Luo, Jian Peng, Jianzhu Ma:
When causal inference meets deep learning. Nat. Mach. Intell. 2(8): 426-427 (2020) - [j17]Yunan Luo, Kaiyu Guan, Jian Peng, Sibo Wang, Yizhi Huang:
STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product. Remote. Sens. 12(19): 3209 (2020) - 2019
- [j16]Yunan Luo, Yun William Yu, Jianyang Zeng, Bonnie Berger, Jian Peng:
Metagenomic binning through low-density hashing. Bioinform. 35(2): 219-226 (2019) - [j15]Sheng Wang, Edward W. Huang, Junmei Cairns, Jian Peng, Liewei Wang, Saurabh Sinha:
Identification of pathways associated with chemosensitivity through network embedding. PLoS Comput. Biol. 15(3) (2019) - [j14]Yufeng Su, Yunan Luo, Xiaoming Zhao, Yang Liu, Jian Peng:
Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction. PLoS Comput. Biol. 15(9) (2019) - 2018
- [j13]Yang Liu, Qing Ye, Liwei Wang, Jian Peng:
Learning structural motif representations for efficient protein structure search. Bioinform. 34(17): i773-i780 (2018) - [j12]Jingbo Shang, Meng Jiang, Wenzhu Tong, Jinfeng Xiao, Jian Peng, Jiawei Han:
DPPred: An Effective Prediction Framework with Concise Discriminative Patterns. IEEE Trans. Knowl. Data Eng. 30(7): 1226-1239 (2018) - 2017
- [j11]Xiuli Ma, Guangyu Zhou, Jingbo Shang, Jingjing Wang, Jian Peng, Jiawei Han:
Detection of Complexes in Biological Networks Through Diversified Dense Subgraph Mining. J. Comput. Biol. 24(9): 923-941 (2017) - [j10]Sheng Wang, Jian Peng:
Network-assisted target identification for haploinsufficiency and homozygous profiling screens. PLoS Comput. Biol. 13(6) (2017) - 2015
- [j9]Sheng Wang, Hyunghoon Cho, ChengXiang Zhai, Bonnie Berger, Jian Peng:
Exploiting ontology graph for predicting sparsely annotated gene function. Bioinform. 31(12): 357-364 (2015) - [j8]Sean Simmons, Jian Peng, Jadwiga R. Bienkowska, Bonnie Berger:
Discovering What Dimensionality Reduction Really Tells Us About RNA-Seq Data. J. Comput. Biol. 22(8): 715-728 (2015) - 2014
- [j7]Emily Berger, Deniz Yörükoglu, Jian Peng, Bonnie Berger:
HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data. PLoS Comput. Biol. 10(3) (2014) - 2013
- [j6]Noah M. Daniels, Andrew Gallant, Jian Peng, Lenore J. Cowen, Michael Baym, Bonnie Berger:
Compressive genomics for protein databases. Bioinform. 29(13): 283-290 (2013) - 2012
- [j5]Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu:
A conditional neural fields model for protein threading. Bioinform. 28(12): 59-66 (2012) - 2011
- [j4]Sheng Wang, Jian Peng, Jinbo Xu:
Alignment of distantly related protein structures: algorithm, bound and implications to homology modeling. Bioinform. 27(18): 2537-2545 (2011) - 2010
- [j3]Jian Peng, Jinbo Xu:
Low-homology protein threading. Bioinform. 26(12): 294-300 (2010) - [j2]Feng Zhao, Jian Peng, Jinbo Xu:
Fragment-free approach to protein folding using conditional neural fields. Bioinform. 26(12): 310-317 (2010) - [j1]Feng Zhao, Jian Peng, Joe DeBartolo, Karl F. Freed, Tobin R. Sosnick, Jinbo Xu:
A Probabilistic and Continuous Model of Protein Conformational Space for Template-Free Modeling. J. Comput. Biol. 17(6): 783-798 (2010)
Conference and Workshop Papers
- 2023
- [c89]Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng, Jianzhu Ma:
3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction. ICLR 2023 - [c88]Shitong Luo, Yufeng Su, Zuofan Wu, Chenpeng Su, Jian Peng, Jianzhu Ma:
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction. ICLR 2023 - [c87]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. ICML 2023: 11827-11846 - [c86]Chaoran Cheng, Jian Peng:
Equivariant Neural Operator Learning with Graphon Convolution. NeurIPS 2023 - [c85]Jiaqi Guan, Xingang Peng, Peiqi Jiang, Yunan Luo, Jian Peng, Jianzhu Ma:
LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion. NeurIPS 2023 - 2022
- [c84]Xinlei Pan, Chaowei Xiao, Warren He, Shuang Yang, Jian Peng, Mingjie Sun, Mingyan Liu, Bo Li, Dawn Song:
Characterizing Attacks on Deep Reinforcement Learning. AAMAS 2022: 1010-1018 - [c83]Shitong Luo, Jiahan Li, Jiaqi Guan, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma:
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing. CVPR 2022: 18910-18919 - [c82]Tanmay Gangwani, Yuan Zhou, Jian Peng:
Imitation Learning from Observations under Transition Model Disparity. ICLR 2022 - [c81]Jiaqi Guan, Wesley Wei Qian, Qiang Liu, Wei-Ying Ma, Jianzhu Ma, Jian Peng:
Energy-Inspired Molecular Conformation Optimization. ICLR 2022 - [c80]Zhizhou Ren, Ruihan Guo, Yuan Zhou, Jian Peng:
Learning Long-Term Reward Redistribution via Randomized Return Decomposition. ICLR 2022 - [c79]Michael Wan, Jian Peng, Tanmay Gangwani:
Hindsight Foresight Relabeling for Meta-Reinforcement Learning. ICLR 2022 - [c78]Beining Han, Zhizhou Ren, Zuofan Wu, Yuan Zhou, Jian Peng:
Off-Policy Reinforcement Learning with Delayed Rewards. ICML 2022: 8280-8303 - [c77]Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie, Jian Peng, Jianzhu Ma:
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets. ICML 2022: 17644-17655 - [c76]Zhizhou Ren, Jiahan Li, Fan Ding, Yuan Zhou, Jianzhu Ma, Jian Peng:
Proximal Exploration for Model-guided Protein Sequence Design. ICML 2022: 18520-18536 - [c75]Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma:
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures. NeurIPS 2022 - [c74]Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma:
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation. NeurIPS 2022 - 2021
- [c73]Yuanyi Zhong, Jianfeng Wang, Lijuan Wang, Jian Peng, Yu-Xiong Wang, Lei Zhang:
DAP: Detection-Aware Pre-Training With Weak Supervision. CVPR 2021: 4537-4546 - [c72]Yuanyi Zhong, Bodi Yuan, Hong Wu, Zhiqiang Yuan, Jian Peng, Yu-Xiong Wang:
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation. ICCV 2021: 7253-7262 - [c71]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. ICLR 2021 - [c70]Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng:
A 3D Generative Model for Structure-Based Drug Design. NeurIPS 2021: 6229-6239 - [c69]Fan Ding, Nan Jiang, Jianzhu Ma, Jian Peng, Jinbo Xu, Yexiang Xue:
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment. UAI 2021: 1100-1109 - 2020
- [c68]Yue Qin, Jian Peng, Yuan Zhou:
A PTAS for the Bayesian Thresholding Bandit Problem. AISTATS 2020: 2455-2464 - [c67]Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu:
Stein Variational Inference for Discrete Distributions. AISTATS 2020: 4563-4572 - [c66]Kefan Dong, Jian Peng, Yining Wang, Yuan Zhou:
Root-n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank. COLT 2020: 1554-1557 - [c65]Tanmay Gangwani, Jian Peng, Yuan Zhou:
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity. CoRL 2020: 2206-2215 - [c64]Yuanyi Zhong, Jianfeng Wang, Jian Peng, Lei Zhang:
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer. ECCV (26) 2020: 615-631 - [c63]Yuanyi Zhong, Alexander G. Schwing, Jian Peng:
Disentangling Controllable Object Through Video Prediction Improves Visual Reinforcement Learning. ICASSP 2020: 3672-3676 - [c62]Tanmay Gangwani, Jian Peng:
State-only Imitation with Transition Dynamics Mismatch. ICLR 2020 - [c61]Xianggen Liu, Qiang Liu, Sen Song, Jian Peng:
A Chance-Constrained Generative Framework for Sequence Optimization. ICML 2020: 6271-6281 - [c60]Tanmay Gangwani, Yuan Zhou, Jian Peng:
Learning Guidance Rewards with Trajectory-space Smoothing. NeurIPS 2020 - [c59]Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng, Qiang Liu:
Off-Policy Interval Estimation with Lipschitz Value Iteration. NeurIPS 2020 - [c58]Yunan Luo, Lam Vo, Hantian Ding, Yufeng Su, Yang Liu, Wesley Wei Qian, Huimin Zhao, Jian Peng:
Evolutionary Context-Integrated Deep Sequence Modeling for Protein Engineering. RECOMB 2020: 261-263 - [c57]Michael Wan, Tanmay Gangwani, Jian Peng:
Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch. UAI 2020: 1218-1227 - [c56]Yuanyi Zhong, Jianfeng Wang, Jian Peng, Lei Zhang:
Anchor Box Optimization for Object Detection. WACV 2020: 1275-1283 - [c55]Volodymyr V. Kindratenko, Dawei Mu, Yan Zhan, John Maloney, Sayed Hadi Hashemi, Benjamin Rabe, Ke Xu, Roy H. Campbell, Jian Peng, William Gropp:
HAL: Computer System for Scalable Deep Learning. PEARC 2020: 41-48 - 2019
- [c54]Hyunghoon Cho, Benjamin Demeo, Jian Peng, Bonnie Berger:
Large-Margin Classification in Hyperbolic Space. AISTATS 2019: 1832-1840 - [c53]Wei-Ye Zhao, Jian Peng:
Stochastic Variance Reduction for Deep Q-learning. AAMAS 2019: 2318-2320 - [c52]Yu He, Yangqiu Song, Jianxin Li, Cheng Ji, Jian Peng, Hao Peng:
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding. CIKM 2019: 639-648 - [c51]Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang:
Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion. ICLR (Poster) 2019 - [c50]Tanmay Gangwani, Qiang Liu, Jian Peng:
Learning Self-Imitating Diverse Policies. ICLR (Poster) 2019 - [c49]Iou-Jen Liu, Jian Peng, Alexander G. Schwing:
Knowledge Flow: Improve Upon Your Teachers. ICLR (Poster) 2019 - [c48]Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng:
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy. ICLR (Poster) 2019 - [c47]Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng:
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization. ICML 2019: 1071-1080 - [c46]ChengYue Gong, Jian Peng, Qiang Liu:
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization. ICML 2019: 2347-2356 - [c45]Chao Tao, Saúl A. Blanco, Jian Peng, Yuan Zhou:
Thresholding Bandit with Optimal Aggregate Regret. NeurIPS 2019: 11659-11668 - [c44]Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng:
Exploration via Hindsight Goal Generation. NeurIPS 2019: 13464-13474 - [c43]Yunan Luo, Jianzhu Ma, Xiaoming Zhao, Yufeng Su, Yang Liu, Trey Ideker, Jian Peng:
Mitigating Data Scarcity in Protein Binding Prediction Using Meta-Learning. RECOMB 2019: 305-307 - [c42]Zhengkai Wu, Evan Johnson, Wei Yang, Osbert Bastani, Dawn Song, Jian Peng, Tao Xie:
REINAM: reinforcement learning for input-grammar inference. ESEC/SIGSOFT FSE 2019: 488-498 - [c41]Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng:
Learning Belief Representations for Imitation Learning in POMDPs. UAI 2019: 1061-1071 - 2018
- [c40]Liyuan Liu, Jingbo Shang, Xiang Ren, Frank Fangzheng Xu, Huan Gui, Jian Peng, Jiawei Han:
Empower Sequence Labeling with Task-Aware Neural Language Model. AAAI 2018: 5253-5260 - [c39]Liyuan Liu, Xiang Ren, Jingbo Shang, Xiaotao Gu, Jian Peng, Jiawei Han:
Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling. EMNLP 2018: 1215-1225 - [c38]Zexuan Zhong, Jiaqi Guo, Wei Yang, Jian Peng, Tao Xie, Jian-Guang Lou, Ting Liu, Dongmei Zhang:
SemRegex: A Semantics-Based Approach for Generating Regular Expressions from Natural Language Specifications. EMNLP 2018: 1608-1618 - [c37]Anusri Pampari, Preethi Raghavan, Jennifer J. Liang, Jian Peng:
emrQA: A Large Corpus for Question Answering on Electronic Medical Records. EMNLP 2018: 2357-2368 - [c36]Tanmay Gangwani, Jian Peng:
Policy Optimization by Genetic Distillation. ICLR (Poster) 2018 - [c35]Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu:
Action-dependent Control Variates for Policy Optimization via Stein Identity. ICLR (Poster) 2018 - [c34]Keyi Yu, Yang Liu, Alexander G. Schwing, Jian Peng:
Fast and Accurate Text Classification: Skimming, Rereading and Early Stopping. ICLR (Workshop) 2018 - [c33]Tianbing Xu, Qiang Liu, Liang Zhao, Jian Peng:
Learning to Explore via Meta-Policy Gradient. ICML 2018: 5459-5468 - [c32]Jiaqi Guan, Yang Liu, Qiang Liu, Jian Peng:
Energy-efficient Amortized Inference with Cascaded Deep Classifiers. IJCAI 2018: 2184-2190 - [c31]Jinglin Chen, Jian Peng, Qiang Liu:
Efficient Localized Inference for Large Graphical Models. IJCAI 2018: 4987-4993 - [c30]Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han:
Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery. ECML/PKDD (2) 2018: 37-54 - [c29]Yunan Luo, Sheng Wang, Jinfeng Xiao, Jian Peng:
Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action. PSB 2018: 44-55 - [c28]Sheng Wang, Jianzhu Ma, Michael Ku Yu, Fan Zheng, Edward W. Huang, Jiawei Han, Jian Peng, Trey Ideker:
Annotating gene sets by mining large literature collections with protein networks. PSB 2018: 601-613 - [c27]Hyunghoon Cho, Bonnie Berger, Jian Peng:
Generalizable Visualization of Mega-Scale Single-Cell Data. RECOMB 2018: 251-253 - [c26]Yunan Luo, Jianzhu Ma, Yang Liu, Qing Ye, Trey Ideker, Jian Peng:
Deciphering Signaling Specificity with Deep Neural Networks. RECOMB 2018: 266-268 - 2017
- [c25]Yihan Gao, Aditya G. Parameswaran, Jian Peng:
On the Interpretability of Conditional Probability Estimates in the Agnostic Setting. AISTATS 2017: 1367-1374 - [c24]Frank S. He, Yang Liu, Alexander G. Schwing, Jian Peng:
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening. ICLR (Poster) 2017 - [c23]Juho Kim, Nate Russell, Jian Peng:
Scalable Visualization for High-dimensional Single-cell Data. PSB 2017 - [c22]Sheng Wang, Meng Qu, Jian Peng:
ProSNet: integrating homology with molecular networks for protein function prediction. PSB 2017: 27-38 - [c21]Yunan Luo, Xinbin Zhao, Jingtian Zhou, Jinling Yang, Yanqing Zhang, Wenhua Kuang, Jian Peng, Ligong Chen, Jianyang Zeng:
A Network Integration Approach for Drug-Target Interaction Prediction and Computational Drug Repositioning from Heterogeneous Information. RECOMB 2017: 383-384 - [c20]Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng:
Stein Variational Policy Gradient. UAI 2017 - 2016
- [c19]Rongda Zhu, Aston Zhang, Jian Peng, Chengxiang Zhai:
Exploiting temporal divergence of topic distributions for event detection. IEEE BigData 2016: 164-171 - [c18]Yunan Luo, Jianyang Zeng, Bonnie Berger, Jian Peng:
Low-Density Locality-Sensitive Hashing Boosts Metagenomic Binning. RECOMB 2016: 255-257 - [c17]Xiuli Ma, Guangyu Zhou, Jingjing Wang, Jian Peng, Jiawei Han:
Complexes Detection in Biological Networks via Diversified Dense Subgraphs Mining. RECOMB 2016: 270-272 - [c16]Jingbo Shang, Jian Peng, Jiawei Han:
MACFP: Maximal Approximate Consecutive Frequent Pattern Mining under Edit Distance. SDM 2016: 558-566 - [c15]Jingbo Shang, Wenzhu Tong, Jian Peng, Jiawei Han:
DPClass: An Effective but Concise Discriminative Patterns-Based Classification Framework. SDM 2016: 567-575 - 2015
- [c14]Qingming Tang, Sheng Wang, Jian Peng, Jianzhu Ma, Jinbo Xu:
Bermuda: de novo assembly of transcripts with new insights for handling uneven coverage. BCB 2015: 166-175 - [c13]Qingming Tang, Chao Yang, Jian Peng, Jinbo Xu:
Exact Hybrid Covariance Thresholding for Joint Graphical Lasso. ECML/PKDD (2) 2015: 593-607 - [c12]Hyunghoon Cho, Bonnie Berger, Jian Peng:
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks. RECOMB 2015: 62-64 - [c11]Qiang Liu, Jian Peng, Alexander Ihler, John W. Fisher III:
Estimating the Partition Function by Discriminance Sampling. UAI 2015: 514-522 - 2014
- [c10]Emily Berger, Deniz Yörükoglu, Jian Peng, Bonnie Berger:
HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data. RECOMB 2014: 18-19 - 2013
- [c9]Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu:
Estimating the Partition Function of Graphical Models Using Langevin Importance Sampling. AISTATS 2013: 433-441 - 2012
- [c8]Qiang Liu, Jian Peng, Alexander Ihler:
Variational Inference for Crowdsourcing. NIPS 2012: 701-709 - [c7]Tamir Hazan, Jian Peng, Amnon Shashua:
Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs. UAI 2012: 356-366 - [c6]Jian Peng, Tamir Hazan, Nathan Srebro, Jinbo Xu:
Approximate Inference by Intersecting Semidefinite Bound and Local Polytope. AISTATS 2012: 868-876 - 2011
- [c5]Jian Peng, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Convex Max-Product over Compact Sets for Protein Folding. ICML 2011: 729-736 - 2010
- [c4]Zhiyong Wang, Feng Zhao, Jian Peng, Jinbo Xu:
Protein 8-class secondary structure prediction using Conditional Neural Fields. BIBM 2010: 109-114 - 2009
- [c3]Jian Peng, Liefeng Bo, Jinbo Xu:
Conditional Neural Fields. NIPS 2009: 1419-1427 - [c2]Jian Peng, Jinbo Xu:
Boosting Protein Threading Accuracy. RECOMB 2009: 31-45 - [c1]Feng Zhao, Jian Peng, Joe DeBartolo, Karl F. Freed, Tobin R. Sosnick, Jinbo Xu:
A Probabilistic Graphical Model for Ab Initio Folding. RECOMB 2009: 59-73
Informal and Other Publications
- 2024
- [i64]Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu:
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. CoRR abs/2403.07902 (2024) - 2023
- [i63]Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng, Jianzhu Ma:
3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction. CoRR abs/2303.03543 (2023) - [i62]Chaoran Cheng, Jian Peng:
Equivariant Neural Operator Learning with Graphon Convolution. CoRR abs/2311.10908 (2023) - 2022
- [i61]Jiahan Li, Shitong Luo, Congyue Deng, Chaoran Cheng, Jiaqi Guan, Leonidas J. Guibas, Jian Peng, Jianzhu Ma:
Directed Weight Neural Networks for Protein Structure Representation Learning. CoRR abs/2201.13299 (2022) - [i60]Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng:
A 3D Molecule Generative Model for Structure-Based Drug Design. CoRR abs/2203.10446 (2022) - [i59]Shitong Luo, Jiahan Li, Jiaqi Guan, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma:
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing. CoRR abs/2203.14486 (2022) - [i58]Tanmay Gangwani, Yuan Zhou, Jian Peng:
Imitation Learning from Observations under Transition Model Disparity. CoRR abs/2204.11446 (2022) - [i57]Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie, Jian Peng, Jianzhu Ma:
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets. CoRR abs/2205.07249 (2022) - [i56]Yuanyi Zhong, Haoran Tang, Junkun Chen, Jian Peng, Yu-Xiong Wang:
Is Self-Supervised Learning More Robust Than Supervised Learning? CoRR abs/2206.05259 (2022) - [i55]Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma:
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation. CoRR abs/2211.10861 (2022) - 2021
- [i54]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. CoRR abs/2102.10240 (2021) - [i53]Yuanyi Zhong, Jianfeng Wang, Lijuan Wang, Jian Peng, Yu-Xiong Wang, Lei Zhang:
DAP: Detection-Aware Pre-training with Weak Supervision. CoRR abs/2103.16651 (2021) - [i52]Beining Han, Zhizhou Ren, Zuofan Wu, Yuan Zhou, Jian Peng:
Off-Policy Reinforcement Learning with Delayed Rewards. CoRR abs/2106.11854 (2021) - [i51]Yuanyi Zhong, Yuan Zhou, Jian Peng:
Coordinate-wise Control Variates for Deep Policy Gradients. CoRR abs/2107.04987 (2021) - [i50]Yuanyi Zhong, Bodi Yuan, Hong Wu, Zhiqiang Yuan, Jian Peng, Yu-Xiong Wang:
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation. CoRR abs/2108.09025 (2021) - [i49]Michael Wan, Jian Peng, Tanmay Gangwani:
Hindsight Foresight Relabeling for Meta-Reinforcement Learning. CoRR abs/2109.09031 (2021) - [i48]Zhizhou Ren, Ruihan Guo, Yuan Zhou, Jian Peng:
Learning Long-Term Reward Redistribution via Randomized Return Decomposition. CoRR abs/2111.13485 (2021) - 2020
- [i47]Carl Yang, Mengxiong Liu, Frank He, Jian Peng, Jiawei Han:
cube2net: Efficient Query-Specific Network Construction with Data Cube Organization. CoRR abs/2002.00841 (2020) - [i46]Yuanyi Zhong, Alexander G. Schwing, Jian Peng:
Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning. CoRR abs/2002.09136 (2020) - [i45]Tanmay Gangwani, Jian Peng:
State-only Imitation with Transition Dynamics Mismatch. CoRR abs/2002.11879 (2020) - [i44]Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu:
Stein Variational Inference for Discrete Distributions. CoRR abs/2003.00605 (2020) - [i43]Michael Wan, Tanmay Gangwani, Jian Peng:
Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch. CoRR abs/2006.07041 (2020) - [i42]Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang:
Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion. CoRR abs/2007.01990 (2020) - [i41]Yuanyi Zhong, Jianfeng Wang, Jian Peng, Lei Zhang:
Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer. CoRR abs/2007.07986 (2020) - [i40]Xianggen Liu, Yunan Luo, Sen Song, Jian Peng:
Pre-training of Graph Neural Network for Modeling Effects of Mutations on Protein-Protein Binding Affinity. CoRR abs/2008.12473 (2020) - [i39]Yuanyi Zhong, Yuan Zhou, Jian Peng:
Efficient Competitive Self-Play Policy Optimization. CoRR abs/2009.06086 (2020) - [i38]Tanmay Gangwani, Yuan Zhou, Jian Peng:
Learning Guidance Rewards with Trajectory-space Smoothing. CoRR abs/2010.12718 (2020) - [i37]Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng, Qiang Liu:
Off-Policy Interval Estimation with Lipschitz Value Iteration. CoRR abs/2010.15392 (2020) - [i36]Tanmay Gangwani, Jian Peng, Yuan Zhou:
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity. CoRR abs/2011.02614 (2020) - 2019
- [i35]Iou-Jen Liu, Jian Peng, Alexander G. Schwing:
Knowledge Flow: Improve Upon Your Teachers. CoRR abs/1904.05878 (2019) - [i34]Wei-Ye Zhao, Xiya Guan, Yang Liu, Xiaoming Zhao, Jian Peng:
Stochastic Variance Reduction for Deep Q-learning. CoRR abs/1905.08152 (2019) - [i33]Chao Tao, Saúl A. Blanco, Jian Peng, Yuan Zhou:
Thresholding Bandit with Optimal Aggregate Regret. CoRR abs/1905.11046 (2019) - [i32]Yang Liu, Yunan Luo, Yuanyi Zhong, Xi Chen, Qiang Liu, Jian Peng:
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning. CoRR abs/1905.13420 (2019) - [i31]Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng:
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization. CoRR abs/1906.03471 (2019) - [i30]Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng:
Exploration via Hindsight Goal Generation. CoRR abs/1906.04279 (2019) - [i29]Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng:
Learning Belief Representations for Imitation Learning in POMDPs. CoRR abs/1906.09510 (2019) - [i28]Chaowei Xiao, Xinlei Pan, Warren He, Jian Peng, Mingjie Sun, Jinfeng Yi, Mingyan Liu, Bo Li, Dawn Song:
Characterizing Attacks on Deep Reinforcement Learning. CoRR abs/1907.09470 (2019) - [i27]Kefan Dong, Jian Peng, Yining Wang, Yuan Zhou:
√n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank. CoRR abs/1909.02506 (2019) - [i26]Yu He, Yangqiu Song, Jianxin Li, Cheng Ji, Jian Peng, Hao Peng:
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding. CoRR abs/1909.03228 (2019) - [i25]Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han:
Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery. CoRR abs/1910.01448 (2019) - [i24]Ke Xu, Kaiyu Guan, Jian Peng, Yunan Luo, Sibo Wang:
DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network. CoRR abs/1911.03607 (2019) - 2018
- [i23]Yihan Gao, Chao Zhang, Jian Peng, Aditya G. Parameswaran:
Low-Norm Graph Embedding. CoRR abs/1802.03560 (2018) - [i22]Tianbing Xu, Qiang Liu, Liang Zhao, Jian Peng:
Learning to Explore with Meta-Policy Gradient. CoRR abs/1803.05044 (2018) - [i21]Liyuan Liu, Xiang Ren, Jingbo Shang, Jian Peng, Jiawei Han:
Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling. CoRR abs/1804.07827 (2018) - [i20]Tanmay Gangwani, Qiang Liu, Jian Peng:
Learning Self-Imitating Diverse Policies. CoRR abs/1805.10309 (2018) - [i19]Hyunghoon Cho, Benjamin Demeo, Jian Peng, Bonnie Berger:
Large-Margin Classification in Hyperbolic Space. CoRR abs/1806.00437 (2018) - [i18]Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng:
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy. CoRR abs/1808.00232 (2018) - [i17]Anusri Pampari, Preethi Raghavan, Jennifer J. Liang, Jian Peng:
emrQA: A Large Corpus for Question Answering on Electronic Medical Records. CoRR abs/1809.00732 (2018) - [i16]Yuanyi Zhong, Jianfeng Wang, Jian Peng, Lei Zhang:
Anchor Box Optimization for Object Detection. CoRR abs/1812.00469 (2018) - 2017
- [i15]Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng:
Stein Variational Policy Gradient. CoRR abs/1704.02399 (2017) - [i14]Liyuan Liu, Jingbo Shang, Frank F. Xu, Xiang Ren, Huan Gui, Jian Peng, Jiawei Han:
Empower Sequence Labeling with Task-Aware Neural Language Model. CoRR abs/1709.04109 (2017) - [i13]Jiaqi Guan, Yang Liu, Qiang Liu, Jian Peng:
Energy-efficient Amortized Inference with Cascaded Deep Classifiers. CoRR abs/1710.03368 (2017) - [i12]Tianbing Xu, Qiang Liu, Jian Peng:
Stochastic Variance Reduction for Policy Gradient Estimation. CoRR abs/1710.06034 (2017) - [i11]Jinglin Chen, Jian Peng, Qiang Liu:
Efficient Localized Inference for Large Graphical Models. CoRR abs/1710.10404 (2017) - [i10]Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu:
Sample-efficient Policy Optimization with Stein Control Variate. CoRR abs/1710.11198 (2017) - [i9]Tanmay Gangwani, Jian Peng:
Genetic Policy Optimization. CoRR abs/1711.01012 (2017) - 2016
- [i8]Xiuli Ma, Guangyu Zhou, Jingjing Wang, Jian Peng, Jiawei Han:
Complexes Detection in Biological Networks via Diversified Dense Subgraphs Mining. CoRR abs/1604.03244 (2016) - [i7]Jingbo Shang, Meng Qu, Jialu Liu, Lance M. Kaplan, Jiawei Han, Jian Peng:
Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks. CoRR abs/1610.09769 (2016) - [i6]Jingbo Shang, Meng Jiang, Wenzhu Tong, Jinfeng Xiao, Jian Peng, Jiawei Han:
DPPred: An Effective Prediction Framework with Concise Discriminative Patterns. CoRR abs/1610.09778 (2016) - [i5]Frank S. He, Yang Liu, Alexander G. Schwing, Jian Peng:
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening. CoRR abs/1611.01606 (2016) - 2015
- [i4]Qingming Tang, Chao Yang, Jian Peng, Jinbo Xu:
Exact Hybrid Covariance Thresholding for Joint Graphical Lasso. CoRR abs/1503.02128 (2015) - [i3]Hyunghoon Cho, Bonnie Berger, Jian Peng:
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks. CoRR abs/1504.02719 (2015) - [i2]Sheng Wang, Jian Peng, Jianzhu Ma, Jinbo Xu:
Protein secondary structure prediction using deep convolutional neural fields. CoRR abs/1512.00843 (2015) - 2012
- [i1]Tamir Hazan, Jian Peng, Amnon Shashua:
Tightening Fractional Covering Upper Bounds on the Partition Function for High-Order Region Graphs. CoRR abs/1210.4881 (2012)
Coauthor Index
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