Noteworthy Preprints:
[World Model]
-
Jiannan Xiang, Guangyi Liu, Yi Gu, Qiyue Gao, Yuting Ning, Yuheng Zha, Zeyu Feng, Tianhua Tao,
Shibo Hao, Yemin Shi, Zhengzhong Liu, E. P. Xing, Zhiting Hu,
PAN: A World Model for General, Interactable, and Long-Horizon World Simulation
,
arXiv:2511.09057, 2025.
-
Shuxian Zou, Tianhua Tao, Sazan Mahbub, Caleb N. Ellington, Robin Algayres, Dian Li, Yonghao Zhuang, Hongyi Wang, Le Song, and E. P. Xing,
A Large-Scale Foundation Model for RNA Function and Structure Prediction
,
NeurIPS AIDrugX Workshop (Spotlight), 2024.
(bioRxiv:10.1101/2024.11.28.625345)
-
Ning Sun, Shuxian Zou, Tianhua Tao, Sazan Mahbub, Xavier Cheng, Yonghao Zhuang, Hongyi Wang, Le Song, and E. P. Xing,
Mixture of Experts Enable Efficient and Effective Protein Understanding and Design
,
NeurIPS AIDrugX Workshop (Spotlight), 2024.
(bioRxiv:10.1101/2024.11.29.625425)
-
Nicholas Ho, Caleb N. Ellington, Jinyu Hou, Sohan Addagudi, Shentong Mo, Tianhua Tao, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, and E. P. Xing,
Scaling Dense Representations for Single Cell with Transcriptome-Scale Context
,
NeurIPS AIDrugX Workshop, 2024.
(bioRxiv:10.1101/2024.11.28.625303)
-
Jiayou Zhang, Barthelemey Meynard-Piganeau, James Gong, Xingyi Cheng, Yingtao Luo, Hugo Ly, Le Song, and E. P. Xing,
Balancing Locality and Reconstruction in Protein Structure Tokenizer
,
NeurIPS Machine Learning in Structural Biology Workshop, 2024.
(bioRxiv:10.1101/2024.12.02.626366)
[Large Language Model]
-
Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Timothy Baldwin, E. P. Xing,
LLM360: Towards Fully Transparent Open-Source LLMs
,
Proceedings of the 1st Conference on Language Modeling (CoLM), 2024.
arXiv:2312.06550.
-
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng,
Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, E. P. Xing,
Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90% ChatGPT Quality
,
Blog, 2023.
- Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Timothy Baldwin, E. P. Xing, LLM360: Towards Fully Transparent Open-Source LLMs,
Proceedings of the 1st Conference on Language Modeling, 2024. (CoLM '24)
- Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, E. P. Xing, Hao Zhang, Joseph E Gonzalez, Ion Stoica, Judging LLM-as-a-judge with MT-bench and Chatbot Arena,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23)
(NeurIPS 23)
- Z. Hu, Z. Yang, X. Liang, R. Salakhutdinov and E. P. Xing, Controllable Text Generation,
The 34th International Conference on Machine Learning.
(ICML 2017).
ALL Publications (in Chronical Order):
2026
-
Yuheng Zha, Kun Zhou, Yujia Wu, Yushu Wang, Jie Feng, Zhi Xu, Shibo Hao, Zhengzhong Liu,
E. P. Xing, Zhiting Hu,
Vision-G1: Towards General Reasoning Vision-Language Models via Reinforcement Learning
,
Fortieth AAAI Conference on Artificial Intelligence, 2026. (AAAI '26)
2025
-
Ding Bai, Shentong Mo, Ruiyi Zhang, Yingtao Luo, Jiahao Gao, Jeremy Yang, Qiuyang Wu, Digvijay Singh,
Hamidreza Rahmani, Tiffany Amariuta, Danielle Grotjahn, Sheng Zhong, Nathan Lewis, Wei Wang,
Trey Ideker, Pengtao Xie, E. P. Xing,
scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics
,
Nature Communications, to appear, 2025.
-
Guy Lutsker, Gal Sapir, Smadar Shilo, Anastasia Godneva, Jerry Greenfield, Dorit Samocha-Bonet,
Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Jordi Merino, Francisco Gude,
Raja Dhir, E. P. Xing, Eran Segal,
A Foundation Model for Continuous Glucose Monitoring Data
,
Nature, to appear, 2025.
-
Lee Reicher, Smadar Shilo, Anastasia Godneva, Hagai Rossman, Guy Lutsker, Liron Zahavi,
Saar Shoer, Zachary Levine, David Krongauz, Rotem Shaulitch, Ayya Keshet, Michal Rein,
Sarah Kohn, Tomer Segev, Yishay Schlesinger, Daniel Barak, Matan Elkan,
Yeela Talmor-Barkan, Yaron Aviv, Yotam Reisner, Adina Weinberger, Le Song,
E. P. Xing, Eran Segal,
The Human Phenotype Project: Deep Phenotyping of the Health-Disease Continuum
,
Nature Medicine, 2025.
-
Mengdi Wang, Zaixi Zhang, Amrit Singh Bedi, Stephanie Guerra, Sheng Lin-Gibson,
Le Cong, Souradip Chakraborty, Yuanhao Qu, Jian Ma, E. P. Xing, George Church,
A Call for Built-in Biosecurity Safeguards for Generative AI Tools
,
Nature Biotechnology, 2025.
-
Xi Fu, Shentong Mo, Alejandro Buendia, Anouchka Laurent, Anqi Shao, Maria del Mar Alvarez-Torres,
Tianji Yu, Jimin Tan, Jiayu Su, Romella Sagatelian, Adolfo Ferrando, Alberto Ciccia, Yanyan Lan,
David Owens, Teresa Palomero, E. P. Xing, Raul Rabadan,
GET: A Foundation Model of Transcription Across Human Cell Types
,
Nature, Volume 637, pages 965-973, 2025.
-
Reza Shahriari, Yichi Yang, Danish N. A. Tamboli, Michael Perez, Yuheng Zha, Jinyu Hou,
Mingkai Deng, Eric D. Ragan, Jaime Ruiz, Daisy Zhe Wang, Zhiting Hu, E. P. Xing,
MuCHEx: A Multimodal Conversational Debugging Tool for Interactive Visual Exploration of Hierarchical Object Classification
,
IEEE Computer Graphics and Applications, 2025.
-
Caleb Ellington, Benjamin Lengerich, Thomas B. K. Watkins, Jiekun Yang, Abhinav K. Adduri,
Sazan Mahbub, Hanxi Xiao, Manolis Kellis, E. P. Xing,
Learning to Estimate Sample-Specific Transcriptional Networks for 7000 Tumors
,
Proceedings of the National Academy of Sciences, 122(21), 2025.
-
Zhenting Qi, Fan Nie, Alexandre Alahi, James Zou, Himabindu Lakkaraju, Yilun Du,
E. P. Xing, Sham M. Kakade, Hanlin Zhang,
In Search of Lost Language Models Training Dynamics
,
Advances in Neural Information Processing Systems 39 (NeurIPS), 2025.
-
Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Youngseog Chung,
Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff Schneider,
Eduard Hovy, Roger Baker Grosse, E. P. Xing,
What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
,
Advances in Neural Information Processing Systems 39 (NeurIPS), 2025.
-
Yiming Gao, Zhen Wang, Jefferson Chen, Mark Antkowiak, Mengzhou Hu,
JungHo Kong, Dexter Pratt, Jieyuan Liu, Enze Ma, Zhiting Hu, E. P. Xing,
scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery
,
Advances in Neural Information Processing Systems 39 (NeurIPS), 2025.
-
Peiyuan Zhang, Haofeng Huang, Yongqi Chen, Will Lin, Zhengzhong Liu, Ion Stoica,
E. P. Xing, Hao Zhang,
Faster Video Diffusion with Trainable Sparse Attention
,
Advances in Neural Information Processing Systems 39, 2025. (NeurIPS '25)
-
Michael Francis Perez, Yichi Yang, Yuheng Zha, Enze Ma, Danish Nisar Ahmed Tamboli, Haodi Ma,
Reza Shahriari, Vyom Pathak, Dzmitry Kasinets, Rohith Venkatakrishnan, Daisy Zhe Wang,
Jaime Ruiz, Eric Ragan, Zhiting Hu, E. P. Xing, Jun-Yan Zhu,
CReLeRI: Explainable, Concept-centric, Representation, Learning, Reasoning, and Interaction Video Analysis System
,
ACM Multimedia 2025 Demo and Video Track. (ACMMM '25)
-
Fan Zhou, Zengzhi Wang, Nikhil Ranjan, Zhoujun Cheng, Liping Tang, Guowei He,
Zhengzhong Liu, E. P. Xing,
MegaMath: Pushing the Limits of Open Math Corpora
,
Proceedings of the 2nd Conference on Language Modeling, 2025. (CoLM '25)
-
Guokan Shang, Hadi Abdine, Ahmad Chamma, Amr Mohamed, Mohamed Anwar,
Abdelaziz Bounhar, Omar El Herraoui, Preslav Nakov, Michalis Vazirgiannis, E. P. Xing,
Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts
,
The Third Arabic Natural Language Processing Conference, 2025.
-
Shaoan Xie, Lingjing Kong, Yujia Zheng, Yu Yao, Zeyu Tang, E. P. Xing, Guangyi Chen, Kun Zhang,
SmartCLIP: Modular Vision-Language Alignment with Identification Guarantees
,
Proceedings of the 37th IEEE Conference on Computer Vision and Pattern Recognition, 2025. (CVPR '25)
-
Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang,
Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, E. P. Xing, Kun Zhang,
Causal Representation Learning from Multimodal Biomedical Observations
,
Proceedings of the 13th International Conference on Learning Representations, 2025. (ICLR '25)
2024
- Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicholas J. Sofroniew, Fabian Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake, How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities, Cell, Volume 187, Issue 25, p7045-7063, December 12, 2024.
- Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, E. P. Xing, Xiaodan Liang, Zhiqiang Shen, Web2Code: A Large-scale Webpage-to- Code Dataset and Evaluation Framework for Multimodal LLMs.,
Advances in Neural Information Processing Systems 38, MIT Press, 2024. (NeurIPS '24)
- Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Timothy Baldwin, E. P. Xing, LLM360: Towards Fully Transparent Open-Source LLMs.,
Proceedings of the 1st Conference on Language Modeling, 2024. (CoLM '24)
- Tianhua Tao, Junbo Li, Bowen Tan, Hongyi Wang, William Marshall, Bhargav M Kanakiya, Joel Hestness, Natalia Vassilieva, Zhiqiang Shen, E. P. Xing, Zhengzhong Liu, Crystal: Illuminating LLM Abilities on Language and Code.,
Proceedings of the 1st Conference on Language Modeling, 2024. (CoLM '24)
- Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui,Julian McAuley, E. P. Xing, Zichao Yang, Zhiting Hu,Generating, Reconstructing, and Representing Discrete and Continuous Data: Generalized Diffusion with Learnable Encoding-Decoding.,
Proceedings of the 41st International Conference on Machine Learning, 2024. (ICML '24)
- Hanlin Zhang, YiFan Zhang, Yaodong Yu, Dhruv Madeka, Dean Foster, E. P. Xing, Himabindu Lakkaraju, Sham M. Kakade, A Study on the Calibration of In-context Learning.,
The 2024 Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL '24)
- Hanoona Abdul Rasheed, Muhammad Maaz, Sahal Shaji Mullappilly, Abdelrahman M Shaker, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, E. P. Xing, Ming-Hsuan Yang, Fahad Khan, GLaMM: Pixel Grounding Large Multimodal Model.,
Proceedings of the 37th IEEE Conference on Computer Vision and Pattern Recognition, 2024. (CVPR '24)
- X. Wang, C. Li, Z. Wang, F. Bai, H. Luo, J. Zhang, N. Jojic, E. P. Xing, Z. Hu, PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization,
Proceedings of 12th International Conference on Learning Representations, 2024. (ICLR 24).
- L. Zheng, W. L. Chiang, Y. Sheng, T. Li, S. Zhuang, Z. Wu, Y. Zhuang, Z. Li, Z. Lin, E. P. Xing, J. E. Gonzalez, I. Stoica, H. Zhang, Lmsys-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset,
Proceedings of 12th International Conference on Learning Representations, 2024. (ICLR 24).
2023
- F. Zhan, Y. Yu, R. Wu, J. Zhang, S. Lu, L. Liu, A. Kortylewsk, C. Theobalt, E. P. Xing, Multimodal Image Synthesis and Editing: A Survey and Taxonomy,
IEEE Transaction on Pattern Analysis and Machine Intelligence, 2023.
- Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, E. P. Xing, Hao Zhang, Joseph E Gonzalez, Ion Stoica, Judging LLM-as-a-judge with MT-bench and Chatbot Arena.,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23).
- X. Song, W. Yao, Y. Fan, X. Dong, G. Chen, J. C. Niebles, E. P. Xing, K. Zhang, Temporally Disentangled Representation Learning under Unknown Nonstationarity,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23).
- K. Liu, F. Zhan, J. Zhang, M. Xu, Y. Yu, A. El Saddik, C. Theobalt, E. P. Xing, S. Lu, Weakly Supervised 3D Open-vocabulary Segmentation,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23).
- S. K. Choe, S. V. Mehta, H. Ahn, W. Neiswanger, P. Xie, E. Strubell, and E. P. Xing, Making Scalable Meta Learning Practical,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23) .
- H. Yan, L. Kong, L. Gui, Y. Chi, E. P. Xing, Y. He, K. Zhang, Counterfactual Generation with Identifiability Guarantee,
Advances in Neural Information Processing Systems 37, MIT Press, 2023. (NeurIPS 23).
- S. Hao, B. Tan, K. Tang, B. Ni, X. Shao, h. Zhang, E. P. Xing, and Z. Hu, BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models,
Proceedings of The 61st Annual Meeting of the Association for Computational Linguistics, 2023. (ACL 23).
- K. Liu, F. Zhan, Y. Chen, J. Zhang, Y. Yu, A. El Saddik, S. Lu, and E. P. Xing, StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields,
Proceedings of the 35th IEEE Conference on Computer Vision and Pattern Recognition, 2023. (CVPR 23).
- A. Xiao, J. Huang, W. Xuan, R. Ren, K. Liu, D. Guan, A. El Saddik, S. Lu, and E. P. Xing, 3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds,
Proceedings of the 35th IEEE Conference on Computer Vision and Pattern Recognition, 2023. (CVPR 23).
- S. Lin, C. Liu, Z. Hu, P. Zhou, S. Wang, R. Zhao, Y. Zheng, L. Lin, E. P. Xing, X. Liang, Prototypical Graph Contrastive Learning,
IEEE Transactions on Neural Networks and Learning Systems, 2022.
- J. Huang, K. Cui, D. Guan, A. Xiao, F. Zhan, S. Lu, S. Liao, and E. P. Xing, Masked Generative Adversarial Networks are Robust Generation Learners,
Advances in Neural Information Processing Systems 36, MIT Press, 2022. (NeurIPS 22).
- K. Sreenivasan, J. Sohn, L. Yang, M. Grinde, A. Nagle, H. Wang, E. P. Xing, K. Lee, and D. Papailiopoulos, Rare Gems: Finding Lottery Tickets at Initialization,
Advances in Neural Information Processing Systems 36, MIT Press, 2022. (NeurIPS 22).
- Z. Shen, Z. Liu and E. P. Xing, Sliced Recursive Transformer,
Proceeding of the 18th European Conference of Computer Vision, 2022. (ECCV 22).
- X. Huang, Z. Shen, S. Li, Z. Liu, X. Hu, J. Wicaksana, E. P. Xing, K-T. Cheng, SDQ: Stochastic Differentiable Quantization with Mixed Precision,
Proceedings of the 39th International Conference on Machine Learning, 2022. (ICML 22).
- M. Zhou, Z. Li, B. Tan, G. Zeng, W. Yang, X. He, Z. Ju, S. Chakravorty, S. Chen, X. Yang, Y. Zhang, Q. Wu, Z. Yu, K. Xu, E. P. Xing, and P. Xie, On the Generation of Medical Dialogs for COVID-19,
Proceedings of The 59th Annual Meeting of the Association for Computational Linguistics, 2021. (ACL '21).
- B. Tan, Z. Yang, M. AI-Shedivat, E. P. Xing, Z. Hu, Progressive Generation of Long Text,
The 2021 Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL '21).
- K. Kandasamy, K. Vysyaraju, W. Neiswanger, B. Paria, C. Collins, J. Schneider, B. Poczos, and E. P. Xing Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly,
Journal of Machine Learning Research, 21 (81), 1-27, 2020.
- K. Tran, W. Neiswanger, J. Yoon, Q. Zhang, E. P. Xing, Z. Ulissi, Methods for comparing uncertainty quantifications for material property predictions,
Machine Learning: Science and Technology, Volume 1, Number 2, 2020.
- Z. Liu, G. Ding, A. Bukkittu, M. Gupta, P. Gao, A. Ahmed, S. Zhang, X. Gao, S. Singhavi, L. Li, W. Wei, Z. Hu, H. Shi, X. Liang, T. Mitamura, E. Xing and Z. Hu. A Data-Centric Framework for Composable NLP Workflows,
Proceeding of the 2020 Conference on Empirical Methods on Natural Language Processing. (EMNLP 2020 Demo).
- X. Zheng, C. Dan, B. Aragam, P. Ravikumar, and E. P. Xing Learning Sparse Nonparametric DAGs,
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020. (AISTATS 20)
- K. Xu, M. Lam, J. Pang, X. Gao, C. Band, P. Mathur, F. Papay, A. K. Khanna, J. B. Cywinski, K. Maheshwari, P. Xie, E. P. Xing, Multimodal Machine Learning for Automated ICD Coding,
Conference on Machine Learning for Healthcare, 2019
(MLCH 2019).
- Y. Li, X. Liang, Z. Hu, Y. Chen, and E. P. Xing, Graph Transformer,
Proceedings of Seventh International Conference on Learning Representations
(ICLR 2019).
- J. Oliva, A. Dubey, M. Zaheer, B. Poczos, R. Salakhutdinov, E. P. Xing and J. Schneider Transformation Autoregressive Networks,
Proceedings of the 35th International Conference on Machine Learning
(ICML '18)
- L. Lee, E. Parisotto, D. S. Chaplot, E. P. Xing and R. Salakhutdinov Gated Path Planning Networks,
Proceedings of the 35th International Conference on Machine Learning
(ICML '18)
- Z. Hu, Z. Yang, X. Liang, R. Salakhutdinov, and E. P. Xing, On Unifying Deep Generative Models,
Proceedings of 6th International Conference on Learning Representations
(ICLR'18)
2017
- S. Lee, N. Gornitz, E. P. Xing, D. Heckerman, C. Lippert Ensembles of Lasso Screening Rules,
IEEE Transaction on Pattern Analysis and Machine Intelligence, 2017 (10.1109/TPAMI.2017.2765321)
- H. Zhang, Z. Deng, X. Liang, L. Yang, S. Xu, J. Zhu, and E. P. Xing, Structured Generative Adversarial Networks,
Proceedings of Advances in Neural Information Processing Systems 31
(NIPS '17). (Recipient of the Nvidia Pioneering Research Award)
- Z. Hu, Z. Yang, X. Liang, R. Salakhutdinov and E. P. Xing, Controllable Text Generation,
The 34th International Conference on Machine Learning.
(ICML 2017).
- X. Liang, L. Lin, X. Shen, J. Feng, S. Yan and E. P. Xing, Interpretable Structure-Evolving LSTM,
Proceedings of the 29th IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2017).
- A. Dubey, J. Oliva, A. Wilson, E. P. Xing, B. Poczos, and J. Schneider, Bayesian Nonparametric Kernel-Learning,
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics.
(AISTATS 2016).
- J. Howrylak, M. Moll, B. Raby, S. Weiss, W. Wu, and E. P. Xing, Gene Expression Profiling of Asthma Phenotypes Demonstrates Molecular Signatures of Atopy and Asthma Control, Journal of Allergy and Clinical Immunology, Volume 137, Issue 5, Pages 1390- 1397, 2016.
- A. Wilson, C. Lucas, C. Dann and E. P. Xing, The Human Kernel,
Advances in Neural Information Processing Systems 29 (eds. Daniel Lee and Masashi Sugiyama), MIT Press, 2015.
(NIPS 2015).
- Z. Hu, P. Huang, Y. Deng, Y. Gao and E. P. Xing,
Entity Hierarchy Embedding,
53rd Annual Meeting of the Association for Computational Linguistics.
(ACL 2015).
- J. Oliva, W. Neiswanger, B. Poczos, E. P. Xing and J. Schneider, Fast Function to Function Regression,
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics.
(AISTATS 2015).
2014
- J. Eisenstein, B. OÂ’Connor, N. A. Smith, and E. P. Xing, Diffusion of Lexical Change in Social Media,
PLoS One, volume 9, Issue 11, e113114, 2014. (
arXiv:1210.5268, communicated 18 Oct 2012.)
[pdf preprint]
- A. Parikh, R. Curtis, I. Kuhn, S. Becker, M. Bissell, E. P. Xing and W. Wu,
Network Analysis of Breast Cancer Progression and Reversal Using a Tree-evolving Network Algorithm, PLoS Computational Biology, Volume 10, Issue 7, e1003713, 2014. [pdf preprint].
- E. P. Xing, R. Curtis, G. Schoenherr, S. Lee, J. Yin, K. Puniyani, W. Wu, P. Kinnaird, GWAS in a Box: Statistical and Visual Analytics of Structured Associations via GenAMap, PLoS One, Volume 9, Issue 6, e97524, 2014. [pdf preprint].
- J. B. Oliva, W. Neiswanger, B. Poczos, J. Schneider and E. P. Xing, Fast Distribution To Real Regression,
Proceedings of the 17th International Conference on Artificial Intelligence and Statistics
(AISTATS 2014).
- J. Zhu and E. P. Xing, Sparse Topical Coding, Proceedings of the 27th International Conference on Conference on Uncertainty in Artificial Intelli- gence (UAI 2011).
-
A. Ahmed, Q. Ho, J. Eisenstein, E. P. Xing, A. Smola and C. H. Teo, Unified Analysis of Streaming News, Proceedings of the International World Wide Web Conference (WWW 2011).
- J. A. Howrylak, T. Dolinay, L. Lucht, Z. Wang, D. C. Christiani, J. M. Sethi1, E. P. Xing, M. P. Donahoe and A. M. K. Choi, Discovery of the gene signature for acute lung injury in patients with sepsis, Physiol. Genomics 37: 133-139, 2009.
- A. F.T. Martins, D. Das, N. A. Smith, and E. P. Xing, Stacking Dependency Parser,
Proceedings of Conference on Empirical Methods in Natural Language Processing, (EMNLP 2008).
- A. Martins, M. Figueiredo, P. Aguiar, N. A. Smith and E. P. Xing,
Nonextensive Entropic Kernels,
Proceedings of the 25th International Conference on Machine Learning (ICML 2008). (A longer version is available soon in CMU-MLD Technical Report 08-106 with the same title.)
- W. Wu and E. P. Xing, A Survey of cDNA Microarray Normalization and a Comparison by k-NN Classification,
in Methods in Microarray Normalization (Ed. S. Phillip), CRC Press. p81-120, 2008.
2006
- F. Guo, W. Fu, Y. Shi and E. P. Xing,
Reverse engineering temporally rewiring gene networks,
The NIPS workshop on New Problems and Methods in Computational Biology
(NIPS2006).
- E.M. Airoldi, D.M. Blei, S.E. Fienberg, E.P. Xing, Latent mixed-membership allocation models of relational and multivariate attribute data, Valencia & ISBA Joint World Meeting on Bayesian Statistics (2006).
- E.P. Xing, R. Sharan and M.I Jordan, Bayesian Haplotype Inference via the Dirichlet Process. Proceedings of the 21st International Conference on Machine Learning (ICML2004), (eds. Greiner and Schuurmans), ACM Press, 879-886, [ps]. An earlier version of this paper also appeared as a book chapter in Lecture Notes in Bioinformatics, Special issue for 2nd RECOMB Satellite Workshop on Computational Methods for SNPs and Haplotypes, 2004. (ps).
- E.P. Xing, A.Y. Ng, M.I. Jordan and S. Russell, Distance Metric Learning, with application to Clustering with side-information,
Advances in Neural Information Processing Systems 16 (NIPS2002),
(eds. Becker et al.) MIT Press, 521-528, 2002. (ps,
data,
code.)
- E.P. Xing, D. Wolf, I. Dubchak, S. Spengler, M. Zorn, C. Kulikowski, I. Muchnik, Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation, Journal of Theoretical Biology, 21;212(2):129-39, 2001.
pre2000
- E.P. Xing, C. Kulikowski, I. Muchnik, I. Dubchak, D. Wolf, S. Spengler and M. Zorn, Analysis of ribosomal RNA sequences by combinatorial clustering, Proceedings, The Seventh International Conference on Intelligence Systems for Molecular Biology (ISMB99),
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