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Posts by Collection
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publications
Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs
Published in The 27th International Conference on Neural Information Processing (ICONIP2020), 2020
This project inspired my interest in machine learning research. Although it was rejected twice due to lack of contribution, it is a very complete work. I am proud of contributing to it.
Recommended citation: Xu, H., Chen, W., Lai, J., Li, Z., Zhao, Y., & Pei, D. (2020). Shallow VAEs with RealNVP Prior can Perform as Well as Deep Hierarchical VAEs. ICONIP. https://link.springer.com/content/pdf/10.1007%2F978-3-030-63823-8_74.pdf
Optimal Mixture Weights for Off-Policy Evaluation with Multiple Behavior Policies
Published in Offline Reinforcement Learning Workshop at Neural Information Processing Systems, 2020
This is my first paper as first author. It is the theory part of my undergraduate dissertation. The paper was rejected by NeurIPS 2020 due to strict assumptions and poor writings. To be honest, I was surprised that the reviewers are not picky about the experiments. They actually indicate that our methods only apply to very short horizon.
Recommended citation: Lai, J., Zou, L., & Song, J. (2020). Optimal Mixture Weights for Off-Policy Evaluation with Multiple Behavior Policies. arXiv preprint arXiv:2011.14359. https://arxiv.org/pdf/2011.14359
Variational Marginal Particle Filters
Published in The 25th International Conference on Artificial Intelligence and Statistics (AISTATS) 2022, 2022
This is my first publication as first author. I enjoy working on it, especially when developing the theories. After the publication, I have made up my mind to contribute more on the theory aspects of machine learning.
Recommended citation: Lai, J., Domke, J., & Sheldon, D. (2022). Variational Marginal Particle Filters. _AISTATS_. https://arxiv.org/pdf/2109.15134.pdf
Automatically Marginalized MCMC in Probabilistic Programming
Published in The 40th International Conference on Machine Learning, 2023
This is my first publication in the field of probabilistic programming. Hope you find it interesting! I personally think that every PPL in the world that has an HMC pipeline should implement this idea.
Recommended citation: Lai, J., Burroni, J., Guan, H., & Sheldon, D. (2023). Automatically Marginalized MCMC in Probabilistic Programming. _ICML_. https://arxiv.org/pdf/2302.00564.pdf
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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