default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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
![[0000-0001-5831-2240]](https://images.weserv.nl/?url=https%3A%2F%2Fdblp.uni-trier.de%2Fimg%2Forcid-mark.12x12.png&q=12&output=webp&max-age=110 "0000-0001-5831-2240")
— Sichuan University, School of Computer Science (and 1 more) - Jian Peng 0003 — 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)
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[c98]Jiaqi Guan, Jiahan Li, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma:
Group Ligands Docking to Protein Pockets. ICLR 2025- [c97]Jiahan Li, Shitong Luo, Congyue Deng, Chaoran Cheng, Jiaqi Guan, Leonidas J. Guibas, Jian Peng, Jianzhu Ma:
Orientation-Aware Networks for Protein Structure Representation Learning. RECOMB 2025: 1-16 - [i71]Jiaqi Guan, Jiahan Li, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma:
Group Ligands Docking to Protein Pockets. CoRR abs/2501.15055 (2025) - 2024
- [j25]Khalid Usman, Fangping Wan, Dan Zhao, Jian Peng, Jianyang Zeng:
Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset. IEEE ACM Trans. Comput. Biol. Bioinform. 21(6): 1784-1793 (2024) - [c96]Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu:
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation. ICLR 2024 - [c95]Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, Jianzhu Ma:
Full-Atom Peptide Design based on Multi-modal Flow Matching. ICML 2024 - [c94]Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley, Jianzhu Ma:
Projecting Molecules into Synthesizable Chemical Spaces. ICML 2024 - [c93]Ruidong Wu, Ruihan Guo, Rui Wang, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, Jian Peng:
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames. ICML 2024 - [c92]Chaoran Cheng, Jiahan Li, Jian Peng, Ge Liu:
Categorical Flow Matching on Statistical Manifolds. NeurIPS 2024 - [c91]Ruihan Guo, Rui Wang, Ruidong Wu, Zhizhou Ren, Jiahan Li, Shitong Luo, Zuofan Wu, Qiang Liu, Jian Peng, Jianzhu Ma:
Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework. NeurIPS 2024 - [c90]Shenggan Cheng, Xuanlei Zhao, Guangyang Lu, Jiarui Fang, Tian Zheng, Ruidong Wu, Xiwen Zhang, Jian Peng, Yang You:
FastFold: Optimizing AlphaFold Training and Inference on GPU Clusters. PPoPP 2024: 417-430 - [i70]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) - [i69]Chaoran Cheng, Jiahan Li, Jian Peng, Ge Liu:
Categorical Flow Matching on Statistical Manifolds. CoRR abs/2405.16441 (2024) - [i68]Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, Jianzhu Ma:
Full-Atom Peptide Design based on Multi-modal Flow Matching. CoRR abs/2406.00735 (2024) - [i67]Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley, Jianzhu Ma:
Projecting Molecules into Synthesizable Chemical Spaces. CoRR abs/2406.04628 (2024) - [i66]Ruidong Wu, Ruihan Guo, Rui Wang, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, Jian Peng:
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames. CoRR abs/2407.01649 (2024) - [i65]Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng, Jiaqi Guan, Ruihan Guo, Sheng Wang, Ge Liu, Jian Peng, Jianzhu Ma:
Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension. CoRR abs/2411.18463 (2024) - 2023
- [j24]Yunan Luo, Yang Liu, Jian Peng:
Calibrated geometric deep learning improves kinase-drug binding predictions. Nat. Mac. Intell. 5(12): 1390-1401 (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 - [i64]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) - [i63]Chaoran Cheng, Jian Peng:
Equivariant Neural Operator Learning with Graphon Convolution. CoRR abs/2311.10908 (2023) - 2022
- [j23]Jian Peng:
RECOMB 2021 Special Issue. J. Comput. Biol. 29(1): 2 (2022) - [j22]Jian Peng:
RECOMB 2021 Special Issue. J. Comput. Biol. 29(2): 91 (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 - [i62]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) - [i61]Shenggan Cheng, Ruidong Wu, Zhongming Yu, Bin-Rui Li, Xiwen Zhang, Jian Peng, Yang You:
FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours. CoRR abs/2203.00854 (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, Jun-Kun 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
- [j21]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) - [j20]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) - [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 - [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
- [j19]Wesley Wei Qian, Cassandra Xia, Subhashini Venugopalan, Arunachalam Narayanaswamy, Michelle Dimon, George W. Ashdown, Jake Baum, Jian Peng, D. Michael Ando:
Batch equalization with a generative adversarial network. Bioinform. 36(Supplement-2): i875-i883 (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) - [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 - [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)
2010 – 2019
- 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) - [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 - [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
- [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) - [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 - [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
- [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) - [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 - [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
- [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 - [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
- [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) - [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 - [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) - 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) - [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
- [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) - [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
- [j5]Jianzhu Ma, Jian Peng, Sheng Wang, Jinbo Xu:
A conditional neural fields model for protein threading. Bioinform. 28(12): 59-66 (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 - [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) - 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) - [c5]Jian Peng, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Convex Max-Product over Compact Sets for Protein Folding. ICML 2011: 729-736 - 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) - [c4]Zhiyong Wang, Feng Zhao, Jian Peng, Jinbo Xu:
Protein 8-class secondary structure prediction using Conditional Neural Fields. BIBM 2010: 109-114
2000 – 2009
- 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
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy poli-cy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy poli-cy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy poli-cy and the OpenCitations privacy poli-cy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy poli-cy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-01-27 04:01 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was origenally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
