一、Weighting-based methods 1.1 balancing weights 1.2 covariate balance 二、Representation-based methods 三、改进1:reweighting与representation的组合拳 3.1 从bound出发 3.2 从representation出发 3.3 从reweighting出发 3.4 小结 四、改进2:谁才是真正的confounders 参考文献 在潜在结果框架的语言下,基于观察数据,在...
We present the state-of-the-art and discuss the methodological differences of these methods, their limitations and recent applications.doi:10.1016/J.SBI.2019.12.018Stefanie KieningerLuca DonatiBettina G KellerElsevier BVCurrent Opinion in Structural Biology...
Monte Carlo methods for phase equilibria of fluids This article presents an overview of Monte Carlo methods for simulations of the phase behaviour of fluids. The Gibbs ensemble method and histogram-reweighting Monte Carlo techniques are described in detail. The Gibbs ensemble method is b... AZ Pan...
【CRR-FMM】A Concise Review of Recent Few-shot Meta-learning Methods 【CRR-FMM】A Concise Review of Recent Few-shot Meta-learning Methods 1 Introduction MindMap 2. The... learner component. Definition 1. (Small-sample learning) Definition 2. (Few-shot learning) Definition智能...
S Tübbicke - 《Journal of Econometric Methods》 被引量: 0发表: 2021年 The impact of nature documentaries on public environmental preferences and willingness to pay: entropy balancing and the blue planet II effect Using entropy balancing, a multivariate reweighting method to produce balanced samples...
[to appear in Proceedings edited by J. Keller, UNAM, Mexico (Kluwer Academic Publ)]William PezzagliaAlfred DifferXxiith International Conference on Differential Geometric Methods in Theoretical Physics
devotedtothedevelopmentofnewMonteCarloalgorithms,suchasclusteralgorithms1,2,3,4andextendedensemblemethods5,6,7,8,9.Forsystemswithdiscretesymmetry,arefinedtreatmentispossibleforthecodingofthecomputerprogram.Forinstance,inthesimulationoftheIsingmodel,onlyonebitisrequiredforstoringtheinformationofasinglespin;a...
Browse State-of-the-Art Datasets Methods More Sign In Few-shot Object Detection via Feature Reweighting ICCV 2019 · Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell · Edit social preview Conventional training of a deep CNN based object detector demands a large ...
First, we show that many commonly used TSCS methods imply an assumption that each unit's non-treatment potential outcomes in the post-treatment period are linear in that unit's pre-treatment outcomes and its time-invariant covariates. Under this assumption, we introduce the mean balancing method...
Classical methods (e.g., force fields) are typically used for FES and present a myriad of challenges, with parametrization being a principle one. On the other hand, parameter-free quantum mechanical (QM) methods tend to be too computationally expensive for adequate sampling. One widely used ...