Hi! I'm a Ph.D. student at the Department of Statistics, Oxford, supervised by Dr. Tom Rainforth and Prof. Yee Whye Teh .
Before that, I was a researcher at Bytedance AI lab, working with Dr. Hao Zhou and Dr. Lei Li.
I'm currently working on topics in machine learning including geometry and symmetry, generative models as well as natural language reasoning.
Publications
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Learning Instance-Specific Augmentations by Capturing Local Invariances
Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim
To appear in ICML, 2023.
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On Incorporating Inductive Biases into VAEs
Ning Miao, Emile Mathieu, Siddharth N, Yee Whye Teh, Tom Rainforth
In ICLR, 2022.
[bib]
[pdf]
[code]
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Do You Have the Right Scissors? Tailoring Pre-trained Language Models via Monte-Carlo Methods
Ning Miao, YuXuan Song, Hao Zhou, Lei Li
In ACL, 2020.
[bib]
[pdf]
[code]
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Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation
Wenxian Shi, Hao Zhou, Ning Miao, Shenjian Zhao, Lei Li
In ICML, 2020.
[bib]
[pdf]
[code]
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Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
YuXuan Song, Ning Miao, Hao Zhou, Lei Li
In AISTATS, 2020.
[bib]
[pdf]
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Kernelized Bayesian Softmax for Text Generation
Ning Miao, Hao Zhou, Chengqi Zhao, Wenxian Shi, Lei Li
In NeurIPS, 2019.
[bib]
[pdf]
[code]
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Generating Fluent Adversarial Examples for Natural Languages
Huangzhao Zhang, Hao Zhou, Ning Miao, Lei Li
In ACL, 2019.
[bib]
[pdf]
[code]
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Constrained Sentence Generation via Metropolis-Hastings Sampling
Ning Miao, Hao Zhou, Lili Mou, Rui Yan, Lei Li
In AAAI, 2019.
[bib]
[pdf]
[code]
Education
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Last updated: Apr 26, 2023