Jian Peng

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Research Output

2020

Characterization of SARS-CoV-2 viral diversity within and across hosts

Sashittal, P., Luo, Y., Peng, J. & El-Kebir, M., May 13 2020, (In preparation) Cold Spring Harbor Laboratory Press, 36 p. (bioRxiv).

Research output: Working paper

Deriving high-spatiotemporal-resolution leaf area index for agroecosystems in the U.S. Corn Belt using Planet Labs CubeSat and STAIR fusion data

Kimm, H., Guan, K., Jiang, C., Peng, B., Gentry, L. F., Wilkin, S. C., Wang, S., Cai, Y., Bernacchi, C. J., Peng, J. & Luo, Y., Mar 15 2020, In : Remote Sensing of Environment. 239, 111615.

Research output: Contribution to journalArticle

Efficient contextualized representation: Language model pruning for sequence labeling

Liu, L., Ren, X., Shang, J., Gu, X., Peng, J. & Han, J., Jan 1 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Riloff, E., Chiang, D., Hockenmaier, J. & Tsujii, J. (eds.). Association for Computational Linguistics, p. 1215-1225 11 p. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

EMRQA: A large corpus for question answering on electronic medical records

Pampari, A., Raghavan, P., Liang, J. & Peng, J., Jan 1 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Riloff, E., Chiang, D., Hockenmaier, J. & Tsujii, J. (eds.). Association for Computational Linguistics, p. 2357-2368 12 p. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Evolutionary context-integrated deep sequence modeling for protein engineering

Luo, Y., Vo, L., Ding, H., Su, Y., Liu, Y., Qian, W. W., Zhao, H. & Peng, J., Jan 1 2020, Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings. Schwartz, R. (ed.). Springer, p. 261-263 3 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12074 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

SemRegex: A semantics-based approach for generating regular expressions from natural language specifications

Zhong, Z., Guo, J., Yang, W., Peng, J., Xie, T., Lou, J. G., Liu, T. & Zhang, D., Jan 1 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Riloff, E., Chiang, D., Hockenmaier, J. & Tsujii, J. (eds.). Association for Computational Linguistics, p. 1608-1618 11 p. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2019

Accelerating nonconvex learning via replica exchange Langevin diffusion

Chen, Y., Chen, J., Dong, J., Peng, J. & Wang, Z., Jan 1 2019.

Research output: Contribution to conferencePaper

A gradual, semi-discrete approach to generative network training via explicit wasserstein minimization

Chen, Y., Telgarsky, M., Zhang, C., Bailey, B., Hsu, D. & Peng, J., Jan 1 2019, 36th International Conference on Machine Learning, ICML 2019. International Machine Learning Society (IMLS), p. 1845-1858 14 p. (36th International Conference on Machine Learning, ICML 2019; vol. 2019-June).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

AstraZeneca-Sanger Drug Combination DREAM Consortium, Dec 1 2019, In : Nature communications. 10, 1, 2674.

Research output: Contribution to journalArticle

Open Access

HetespaceyWalk: A heterogeneous Spacey random walk for heterogeneous information network embedding

He, Y., Song, Y., Li, J., Ji, C., Peng, J. & Peng, H., Nov 3 2019, CIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 639-648 10 p. (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access

Identification of pathways associated with chemosensitivity through network embedding

Wang, S., Huang, E., Cairns, J., Peng, J., Wang, L. & Sinha, S., Mar 2019, In : PLoS computational biology. 15, 3, e1006864.

Research output: Contribution to journalArticle

Open Access

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Cai, Y., Guan, K., Lobell, D., Potgieter, A. B., Wang, S., Peng, J., Xu, T., Asseng, S., Zhang, Y., You, L. & Peng, B., Aug 15 2019, In : Agricultural and Forest Meteorology. 274, p. 144-159 16 p.

Research output: Contribution to journalArticle

Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction

Su, Y., Luo, Y., Zhao, X., Liu, Y. & Peng, J., Jan 1 2019, In : PLoS computational biology. 15, 9, e1007283.

Research output: Contribution to journalArticle

Open Access

Learning to play in a day: Faster deep reinforcement learning by optimality tightening

He, F. S., Liu, Y., Schwing, A. G. & Peng, J., Jan 1 2019.

Research output: Contribution to conferencePaper

Metagenomic binning through low-density hashing

Luo, Y., Yu, Y. W., Zeng, J., Berger, B. & Peng, J., Jan 15 2019, In : Bioinformatics. 35, 2, p. 219-226 8 p.

Research output: Contribution to journalArticle

Open Access

Off-policy evaluation and learning from logged bandit feedback: Error reduction via surrogate policy

Xie, Y., Liu, Q., Zhou, Y., Liu, B., Wang, Z. & Peng, J., Jan 1 2019.

Research output: Contribution to conferencePaper

Quantite Stein variational gradient descent for batch Bayesian optimization

Gong, C., Peng, J. & Liu, Q., Jan 1 2019, 36th International Conference on Machine Learning, ICML 2019. International Machine Learning Society (IMLS), p. 4212-4221 10 p. (36th International Conference on Machine Learning, ICML 2019; vol. 2019-June).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

REINAM: Reinforcement learning for input-grammar inference

Wu, Z., Johnson, E., Yang, W., Bastani, O., Song, D., Peng, J. & Xie, T., Aug 12 2019, ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Apel, S., Dumas, M., Russo, A. & Pfahl, D. (eds.). Association for Computing Machinery, Inc, p. 488-498 11 p. (ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Robust single-cell Hi-C clustering by convolution- And random-walk–based imputation

Zhou, J., Ma, J., Chen, Y., Cheng, C., Bao, B., Peng, J., Sejnowski, T. J., Dixon, J. R. & Ecker, J. R., Jan 1 2019, In : Proceedings of the National Academy of Sciences of the United States of America. 116, 28, p. 14011-14018 8 p.

Research output: Contribution to journalArticle

Open Access

Similarity modeling on heterogeneous networks via automatic path discovery

Yang, C., Liu, M., He, F., Zhang, X., Peng, J. & Han, J., Jan 1 2019, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Proceedings. Bonchi, F., Berlingerio, M., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Springer-Verlag Berlin Heidelberg, p. 37-54 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11052 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Stochastic variance reduction for deep Q-iearning

Zhao, W. Y. & Peng, J., Jan 1 2019, 18th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2019. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), p. 2318-2320 3 p. (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; vol. 4).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Stratification of amyotrophic lateral sclerosis patients: A crowdsourcing approach

The ALS Stratification Consortium & Peng, J., Jan 1 2019, In : Scientific reports. 9, 1, 690.

Research output: Contribution to journalArticle

Open Access

Toward building a transparent statistical model for improving crop yield prediction: Modeling rainfed corn in the U.S

Li, Y., Guan, K., Yu, A., Peng, B., Zhao, L., Li, B. & Peng, J., Mar 15 2019, In : Field Crops Research. 234, p. 55-65 11 p.

Research output: Contribution to journalArticle

2018

Action-dependent control variates for policy optimization via Stein’s identity

Liu, H., Feng, Y., Mao, Y., Zhou, D., Peng, J. & Liu, Q., Jan 1 2018.

Research output: Contribution to conferencePaper

A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

Cai, Y., Guan, K., Peng, J., Wang, S., Seifert, C., Wardlow, B. & Li, Z., Jun 1 2018, In : Remote Sensing of Environment. 210, p. 35-47 13 p.

Research output: Contribution to journalArticle

Annotating gene sets by mining large literature collections with protein networks

Wang, S., Ma, J., Yu, M. K., Zheng, F., Huang, E. W., Han, J., Peng, J. & Ideker, T., Jan 1 2018, In : Pacific Symposium on Biocomputing. 0, 212669, p. 602-613 12 p.

Research output: Contribution to journalConference article

Deciphering signaling specificity with deep neural networks

Luo, Y., Ma, J., Liu, Y., Ye, Q., Ideker, T. & Peng, J., Jan 1 2018, Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. Raphael, B. J. (ed.). Springer-Verlag Berlin Heidelberg, p. 266-268 3 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10812 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

DPPred: An Effective Prediction Framework with Concise Discriminative Patterns

Shang, J., Jiang, M., Tong, W., Xiao, J., Peng, J. & Han, J., Jul 1 2018, In : IEEE Transactions on Knowledge and Data Engineering. 30, 7, p. 1226-1239 14 p.

Research output: Contribution to journalArticle

Efficient localized inference for large graphical models

Chen, J., Peng, J. & Liu, Q., Jan 1 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 4987-4993 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Empower sequence labeling with task-aware neural language model

Liu, L., Shang, J., Ren, X., Xu, F. F., Gui, H., Peng, J. & Han, J., Jan 1 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI Press, p. 5253-5260 8 p. (32nd AAAI Conference on Artificial Intelligence, AAAI 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Energy-efficient amortized inference with cascaded deep classifiers

Guan, J., Liu, Y., Liu, Q. & Peng, J., Jan 1 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 2184-2190 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks

Liu, Y., Palmedo, P., Ye, Q., Berger, B. & Peng, J., Jan 24 2018, In : Cell Systems. 6, 1, p. 65-74.e3

Research output: Contribution to journalArticle

Fast and accurate text classification: Skimming, rereading and early stopping

Yu, K., Liu, Y., Schwing, A. G. & Peng, J., Jan 1 2018.

Research output: Contribution to conferencePaper

Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks

Cho, H., Berger, B. & Peng, J., Aug 22 2018, In : Cell Systems. 7, 2, p. 185-191.e4

Research output: Contribution to journalArticle

Generalizable visualization of mega-scale single-cell data

Cho, H., Berger, B. & Peng, J., Jan 1 2018, Research in Computational Molecular Biology - 22nd Annual International Conference, RECOMB 2018, Proceedings. Raphael, B. J. (ed.). Springer-Verlag Berlin Heidelberg, p. 251-253 3 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10812 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action

Luo, Y., Wang, S., Xiao, J. & Peng, J., Jan 1 2018, In : Pacific Symposium on Biocomputing. 0, 212669, p. 44-55 12 p.

Research output: Contribution to journalConference article

Learning structural motif representations for efficient protein structure search

Liu, Y., Ye, Q., Wang, L. & Peng, J., Sep 1 2018, In : Bioinformatics. 34, 17, p. i773-i780

Research output: Contribution to journalArticle

Learning to explore via meta-policy gradient

Xu, T., Liu, Q., Zhao, L. & Peng, J., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 8686-8706 21 p. (35th International Conference on Machine Learning, ICML 2018; vol. 12).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Policy optimization by genetic distillation

Gangwani, T. & Peng, J., Jan 1 2018.

Research output: Contribution to conferencePaper

Reconstructing spatial organizations of chromosomes through manifold learning

Zhu, G., Deng, W., Hu, H., Ma, R., Zhang, S., Yang, J., Peng, J., Kaplan, T. & Zeng, J., May 4 2018, In : Nucleic acids research. 46, 8, p. e50

Research output: Contribution to journalArticle

Open Access

Typing tumors using pathways selected by somatic evolution

Wang, S., Ma, J., Zhang, W., Shen, J. P., Huang, J., Peng, J. & Ideker, T., Dec 1 2018, In : Nature communications. 9, 1, 4159.

Research output: Contribution to journalArticle

2017

A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration- resistant prostate cancer

Prostate Cancer DREAM Challenge Community, Jan 1 2017, In : JCO Clinical Cancer Informatics. 2017, 1, p. 1-15 15 p.

Research output: Contribution to journalArticle

Open Access

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

Luo, Y., Zhao, X., Zhou, J., Yang, J., Zhang, Y., Kuang, W., Peng, J., Chen, L. & Zeng, J., Dec 1 2017, In : Nature communications. 8, 1, 573.

Research output: Contribution to journalArticle

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

Luo, Y., Zhao, X., Zhou, J., Yang, J., Zhang, Y., Kuang, W., Peng, J., Chen, L. & Zeng, J., Jan 1 2017, Research in Computational Molecular Biology - 21st Annual International Conference, RECOMB 2017, Proceedings. Sahinalp, S. C. (ed.). Springer-Verlag Berlin Heidelberg, p. 383-384 2 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10229 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Detection of complexes in biological networks through diversified dense subgraph mining

Ma, X., Zhou, G., Shang, J., Wang, J., Peng, J. & Han, J., Sep 2017, In : Journal of Computational Biology. 24, 9, p. 923-941 19 p.

Research output: Contribution to journalArticle

Genome-Scale Networks Link Neurodegenerative Disease Genes to α-Synuclein through Specific Molecular Pathways

Khurana, V., Peng, J., Chung, C. Y., Auluck, P. K., Fanning, S., Tardiff, D. F., Bartels, T., Koeva, M., Eichhorn, S. W., Benyamini, H., Lou, Y., Nutter-Upham, A., Baru, V., Freyzon, Y., Tuncbag, N., Costanzo, M., San Luis, B. J., Schöndorf, D. C., Barrasa, M. I., Ehsani, S. & 10 others, Sanjana, N., Zhong, Q., Gasser, T., Bartel, D. P., Vidal, M., Deleidi, M., Boone, C., Fraenkel, E., Berger, B. & Lindquist, S., Feb 22 2017, In : Cell Systems. 4, 2, p. 157-170.e14

Research output: Contribution to journalArticle

Network-assisted target identification for haploinsufficiency and homozygous profiling screens

Wang, S. & Peng, J., Jun 2017, In : PLoS computational biology. 13, 6, e1005553.

Research output: Contribution to journalArticle

On the interpretability of conditional probability estimates in the agnostic setting

Gao, Y., Parameswaran, A. & Peng, J., Jan 1 2017, In : Electronic Journal of Statistics. 11, 2, p. 5198-5231 34 p.

Research output: Contribution to journalArticle

ProSNet: Integrating homology with molecular networks for protein function prediction

Wang, S., Qu, M. & Peng, J., Jan 1 2017, PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017. Altman, R. B., Murray, T., Klein, T. E., Dunker, A. K., Ritchie, M. D. & Hunter, L. (eds.). 212679 ed. World Scientific Publishing Co. Pte Ltd, p. 27-38 12 p. (Pacific Symposium on Biocomputing, 2017; no. 212679).

Research output: Chapter in Book/Report/Conference proceedingConference contribution