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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
Paper Reviews LLMs achieve adult human performance on higher-order theory of mind tasks
Published:
Just read through a paper from Arxiv. This topic is very interesting. “High order theory of mind”: the human ability to reason about multiple mental and emotional states in a recursive manner (e.g. I think that you believe that she knows). This step by step recursive reasoning should be what AI are good at since they should be good at recursively applying the same logic. The issue is to save within the AI framework, any mid-results that is found.
Consider Bayesian Posterior from a diffusion perspective
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If one looks very carefully at how diffusion models equation is written down. It is very clear that there is connection between Bayesian Posterior and current diffusion Model. In Bayesian Statistics, we have $\theta \sim \pi(\theta)$ and ${\bf X} = {x_1,\cdots x_T} \sim f(x\mid \theta)$
A new introduction
Published:
Dear Readers of my technical blogpost, if you ever have the chance to come to this point. Well, first thing, thanks for coming to my blog series where I have decided to write about what I read over the years and pick out something interesting. I have done similar work before but it failed partially due to the fact that I was not able to be productive. In fact, I am pretty bad and maintaining something with positive feedback so maybe I will share this work on Medium or whatever platform neccesary to maintain a positive feedback loop. At the moment, I am thinking about just making this as a piece of notetaker for the papers that I have read. I will summarize the ideas in the paper but I will try not to comment on the work unless I have the oppportunity to play with properly. This blog series will mainly focus on
portfolio
Deep Learning for System Biology
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Deep Neural Networks in our cells
ABC Methods
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Approximate Bayesian Computation, a solution to interestingly hard problems
publications
Efficient Hybrid Algorithms for Computing Clusters Overlap
Published in Procedia Computer Science, 2016
we come up with a fast probabilistic algorithm,…, that can determine the similarity between large segments with a higher degree of accuracy than other known methods.
Recommended citation: Javangula, P., Modarre, K., Shenoy, P., Liu, Y., & Nayebi, A. (2017). " Efficient Hybrid Algorithms for Computing Clusters Overlap 1." Procedia Computer Science. 108: 1050-1059. https://www.sciencedirect.com/science/article/pii/S1877050917308050
Variable Selection with ABC Bayesian Forests
Published in Journal of Royal Statistical Society Series B (in Press), 2020
This paper develops the methodology for variable selection under non-parametric setting using ABC.
Recommended citation: Liu Y, Ročková V, Wang Y (2020). "Variable Selection with ABC Bayesian Forests." Journal of Royal Statistical Society Series B, In Press . https://arxiv.org/abs/1806.02304
Variable Selection via Thompson Sampling
Published in Jounal of America Statistical Association (In Press), Winner of SBSS 2020 Student Paper Competition awarded by ASA, 2020
TVS brings together Bayesian reinforcement and machine learning in order to extend the reach of Bayesian subset selection to non-parametric models and large datasets with very many predictors and/or very many observations.
Recommended citation: Liu Y., Rockova, V. . Variable Selection via Thompson Sampling[J]." arXiv preprint arXiv:2007.00187, 2020. . 1(3). https://yiliu9090.github.io/files/VS_TS.pdf
Fully Interpretable Deep Learning Model of Transcriptional Control
Published in ISMB 2020, 2020
This paper demonstrate that a case of fully interpretable Deep Learning Model
Recommended citation: Liu Y, Barr K, Reinitz J. (2019). " Fully Interpretable Deep Learning Model of Transcriptional Control[J]." Bioinformatics, Volume 36, Issue Supplement_1, July 2020, Pages i499–i507, Published . 1(3). https://academic.oup.com/bioinformatics/article/36/Supplement_1/i499/5870526
talks
Mini-Siminar
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A departmental mini-siminar organized for year 2 students with a focus on past research and current research directions. The focus of the presentation lies in the current work in ABC Variable Selections Methods. Link to the Slides
Presentation on Deep Learning for Genomics
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This talk is class presentation for Computational Biology Class. However the content of the talk focuses on my recent work in Fully Interpretable Deep Learning Model of Transcriptional Control
Presentation at ISMB
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This talk is for ISMB. However the content of the talk focuses on my work in Fully Interpretable Deep Learning Model of Transcriptional Control
teaching
Teaching Assistant
Teaching Assistant, University of Chicago, Department of Statistics, 2019
Teaching Assistant to STAT 24400: Link to Course Website cleared due to webpage upgrades