Jie Ren
Affiliations:- Google Brain, CA, USA
- University of Southern California, Department of Biological Sciences, Los Angeles, CA, USA (PhD 2017)
- Peking University, Department of Probability and Statistics, Beijing, China
According to our database1,
Jie Ren
authored at least 30 papers
between 2012 and 2023.
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Bibliography
2023
J. Mach. Learn. Res., 2023
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models.
CoRR, 2023
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models.
Proceedings of the International Conference on Machine Learning, 2023
Out-of-Distribution Detection and Selective Generation for Conditional Language Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Does your dermatology classifier know what it doesn't know? Detecting the long-tail of unseen conditions.
Medical Image Anal., 2022
A New Context Tree Inference Algorithm for Variable Length Markov Chain Model with Applications to Biological Sequence Analyses.
J. Comput. Biol., 2022
2021
CoRR, 2021
KIMI: Knockoff Inference for Motif Identification from molecular sequences with controlled false discovery rate.
Bioinform., 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data.
Quant. Biol., 2020
Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments.
J. Comput. Biol., 2020
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks.
CoRR, 2020
2019
SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders.
CoRR, 2019
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
2017
BMC Bioinform., 2017
2016
Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics.
Bioinform., 2016
2014
New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing.
Briefings Bioinform., 2014
2013
J. Comput. Biol., 2013
2012
Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract.
Proceedings of the Research in Computational Molecular Biology, 2012