1 code implementation • 17 Apr 2024 • Yue Wu, Yewen Fan, So Yeon Min, Shrimai Prabhumoye, Stephen Mcaleer, Yonatan Bisk, Ruslan Salakhutdinov, Yuanzhi Li, Tom Mitchell
The chains of nodes can be designed to explicitly enforce a naturally structured "thought process".
no code implementations • 30 Jan 2024 • Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang
The metric variance comes from the randomness inherent in the training process of deep learning pipelines.
no code implementations • 28 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.
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.
no code implementations • 19 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.
1 code implementation • 19 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.