JSM 2022 후기
JSM 2022 후기
JSM은 Joint Statistical Meetings 의 약자로 전세계 통계학자들이 모이는 가장 큰 학회이다. 나는 이번 학회에 포스터 발표를 하게 되었는데, 다녀와서 느낀 점을 남겨보고자 한다.
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- 8/7 (Sun)
- Bayesian Modeling Of Spatial Transcriptomics via Gaussian Process (Boost-GP) : https://github.com/Minzhe/BOOST-GP
- Ising model (Identify an SV gene via fitting an Ising model to dichotomized expression levels) : A model of interacting binary spins on a lattice.
- 8/8 (Mon)
- A spatial Bayesian Latent Factor Model for Image-on-Image Regression by Jian Kang
- Use rfMRI, sMRI to predict fMRI
- Deep-learning: Image-to-image translation. Conditional adversarial network
- Outcome image -> basis coefficient by Gaussian process -> latent variable by spatially latent model -> predicting image
- 8/9 (Tue)
- In remembrance of the life and legacy of Marshall Joffe
- Mortal Multi-Armed Bandit problem
- Hangover ...
- 8/10 (Wed)
- Faster Estimation for Constrained Gamma Mixture Models Using Close-Form Estimators by Jiangmei Xiong
- Impose the location of the mode to derive the closed-form estimator for gamma distribution
- 8/11 (Thu)
- Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by Andrew Brown
- Gaussian Markov Random Field to smooth out
- An All-In-One Statistical Framework That Generates Realistic Single-Cell Omics Data and Infers Cell Heterogeneity Structure by Jingyi Li (and my friend Dong Yuan Song)
- scDesign3: transcriptomics 같은것도 simulation 가능해졌다
(초기버젼: https://github.com/Vivianstats/scDesign)
- 느낀점
- 다음 포스터 세션할 때는 컴퓨터를 가져와서 모델이 어떻게 작동하는지 보여주기 (Cell tracking method 특히)
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- Museum of American History
- Museum of Arts
- Apple store in Carnegie library
- Rasika
- Capitol Hill
- Lab dinner at Zaytinya
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