21 citations · 43 across the 5 of their papers we have counts for
10 papers · 1 filter
Point process models for sequence detection in high-dimensional neural spike trains
Alex H. Williams, Anthony Degleris, Yixin Wang +1
Sparse sequences of neural spikes are posited to underlie aspects of working memory, motor production, and learning. Discovering these sequences in an unsupervised manner is a long…
Towards Clarifying the Theory of the Deconfounder
Yixin Wang, David M. Blei
Wang and Blei (2019) studies multiple causal inference and proposes the deconfounder algorithm. The paper discusses theoretical requirements and presents empirical studies. Several…
The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019)
Yixin Wang, David M. Blei
Ogburn et al. (2019, arXiv:1910.05438) discuss "The Blessings of Multiple Causes" (Wang and Blei, 2018, arXiv:1805.06826). Many of their remarks are interesting. But they also clai…
Multiple Causes: A Causal Graphical View
Yixin Wang, David M. Blei
Unobserved confounding is a major hurdle for causal inference from observational data. Confounders---the variables that affect both the causes and the outcome---induce spurious non…
Equal Opportunity and Affirmative Action via Counterfactual Predictions
Yixin Wang, Dhanya Sridhar, David M. Blei
Machine learning (ML) can automate decision-making by learning to predict decisions from historical data. However, these predictors may inherit discriminatory policies from past de…
Variational Bayes under Model Misspecification
Yixin Wang, David M. Blei
Variational Bayes (VB) is a scalable alternative to Markov chain Monte Carlo (MCMC) for Bayesian posterior inference. Though popular, VB comes with few theoretical guarantees, most…