Jie Ren

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 37

Top Topics

Mahalanobis Distance

Top Venues

J. Comput. Biol.

Publications

James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Jeremiah Zhe Liu, Xiuye Gu, Yin Cui, Dustin Tran, Balaji Lakshminarayanan
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. CoRR (2023)
James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. ICML (2023)
Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu, Balaji Lakshminarayanan
Self-Evaluation Improves Selective Generation in Large Language Models. CoRR (2023)
Yunhao Ge, Jie Ren, Jiaping Zhao, Kaifeng Chen, Andrew Gallagher, Laurent Itti, Balaji Lakshminarayanan
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models. CoRR (2023)
Jie Ren, Yao Zhao, Tu Vu, Peter J. Liu, Balaji Lakshminarayanan
Self-Evaluation Improves Selective Generation in Large Language Models. ICBINB (2023)
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. J. Mach. Learn. Res. 24 (2023)
Benoit Dherin, Huiyi Hu, Jie Ren, Michael W. Dusenberry, Balaji Lakshminarayanan
Morse Neural Networks for Uncertainty Quantification. CoRR (2023)
Yunhao Ge, Jie Ren, Andrew Gallagher, Yuxiao Wang, Ming-Hsuan Yang, Hartwig Adam, Laurent Itti, Balaji Lakshminarayanan, Jiaping Zhao
Improving Zero-shot Generalization and Robustness of Multi-Modal Models. CVPR (2023)
Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Z. Liu
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study. EMNLP (Findings) (2023)
Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Z. Liu
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study. CoRR (2023)
Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise. EMNLP (Findings) (2023)
Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J. Liu
Out-of-Distribution Detection and Selective Generation for Conditional Language Models. ICLR (2023)
Yunhao Ge, Jie Ren, Yuxiao Wang, Andrew Gallagher, Ming-Hsuan Yang, Laurent Itti, Hartwig Adam, Balaji Lakshminarayanan, Jiaping Zhao
Improving Zero-shot Generalization and Robustness of Multi-modal Models. CoRR (2022)
Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise. CoRR (2022)
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions. Medical Image Anal. 75 (2022)
Shaokun An, Jie Ren, Fengzhu Sun, Lin Wan
A New Context Tree Inference Algorithm for Variable Length Markov Chain Model with Applications to Biological Sequence Analyses. J. Comput. Biol. 29 (8) (2022)
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness. CoRR (2022)
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan
Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR (2022)
Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh, Balaji Lakshminarayanan, Peter J. Liu
Out-of-Distribution Detection and Selective Generation for Conditional Language Models. CoRR (2022)
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zachary Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Gregory S. Corrado, Umesh Telang, Yun Liu, A. Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions. CoRR (2021)
Xin Bai, Jie Ren, Yingying Fan, Fengzhu Sun
KIMI: Knockoff Inference for Motif Identification from molecular sequences with controlled false discovery rate. Bioinform. 37 (6) (2021)
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan
Exploring the Limits of Out-of-Distribution Detection. CoRR (2021)
Jie Ren, Stanislav Fort, Jeremiah Liu, Abhijit Guha Roy, Shreyas Padhy, Balaji Lakshminarayanan
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection. CoRR (2021)
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR (2021)
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan
Exploring the Limits of Out-of-Distribution Detection. NeurIPS (2021)
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Z. Liu, Jasper Snoek, Balaji Lakshminarayanan
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks. CoRR (2020)
Chao Deng, Timothy Daley, Peter Calabrese, Jie Ren, Andrew D. Smith
Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments. J. Comput. Biol. 27 (7) (2020)
Jie Ren, Kai Song, Chao Deng, Nathan A. Ahlgren, Jed A. Fuhrman, Yi Li, Xiaohui Xie, Ryan Poplin, Fengzhu Sun
Identifying viruses from metagenomic data using deep learning. Quant. Biol. 8 (1) (2020)
Lin Wan, Xin Kang, Jie Ren, Fengzhu Sun
Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data. Quant. Biol. 8 (2) (2020)
Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. CoRR (2019)
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR (2019)
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan
Likelihood Ratios for Out-of-Distribution Detection. NeurIPS (2019)
Peter J. Liu, Yu-An Chung, Jie Ren
SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders. CoRR (2019)
Yang Young Lu, Kujin Tang, Jie Ren, Jed A. Fuhrman, Michael S. Waterman, Fengzhu Sun
CAFE: aCcelerated Alignment-FrEe sequence analysis. Nucleic Acids Res. 45 (Webserver-Issue) (2017)
Mengge Zhang, Lianping Yang, Jie Ren, Nathan A. Ahlgren, Jed A. Fuhrman, Fengzhu Sun
Prediction of virus-host infectious association by supervised learning methods. BMC Bioinform. 18 (S-3) (2017)
Jie Ren, Kai Song, Minghua Deng, Gesine Reinert, Charles H. Cannon, Fengzhu Sun
Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. Bioinform. 32 (7) (2016)
Kai Song, Jie Ren, Gesine Reinert, Minghua Deng, Michael S. Waterman, Fengzhu Sun
New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. Briefings Bioinform. 15 (3) (2014)
Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun
Alignment-Free Sequence Comparison Based on Next-Generation Sequencing Reads. J. Comput. Biol. 20 (2) (2013)
Jie Ren, Kai Song, Fengzhu Sun, Minghua Deng, Gesine Reinert
Multiple alignment-free sequence comparison. Bioinform. 29 (21) (2013)
Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng, Fengzhu Sun
Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract. RECOMB (2012)