Search Results for author: Yewen Fan

Found 5 papers, 2 papers with code

On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors

no code implementations28 Dec 2023 Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin, Sathyamoorthy Rajendran, Kun Zhang

Financial data is generally time series in essence and thus suffers from three fundamental issues: the mismatch in time resolution, the time-varying property of the distribution - nonstationarity, and causal factors that are important but unknown/unobserved.

Time Series

Temporally Disentangled Representation Learning under Unknown Nonstationarity

1 code implementation NeurIPS 2023 Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric Xing, Kun Zhang

In unsupervised causal representation learning for sequential data with time-delayed latent causal influences, strong identifiability results for the disentanglement of causally-related latent variables have been established in stationary settings by leveraging temporal structure.

Disentanglement

Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks

no code implementations19 May 2023 Yujia Zheng, Ignavier Ng, Yewen Fan, Kun Zhang

A Markov network characterizes the conditional independence structure, or Markov property, among a set of random variables.

Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems

1 code implementation19 May 2022 Yewen Fan, Nian Si, Kun Zhang

Calibration is defined as the ratio of the average predicted click rate to the true click rate.

Recommendation Systems

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