# Automated Predictive Evaluation of Causal Inference Competitions

May 30, 2019       4 mins     Tag: causal
We can evaluate causal inference methods through simulations and based on predictive performance of ATE, but is it enough?

# The Optimal Transport and Importance Sampling

May 22, 2019       3 mins     Tag: ad-hoc computation
Most statisticians-orientated introduction to optimal transport theory starts with the motivation: we can always obtain a one-D distribution $f(\theta)$ through its inverse cdf transformation

# Affordable Bayesian Neural Networks

May 20, 2019       10 mins     Tag: computation
We wrote a new paper on approximate Bayesian inference in deep network, with a similiar computation cost as point estimation.

# Something I learned from the book "shortest way home"

May 01, 2019       4 mins     Tag: politics
A new book by the interesting candidate, Mayor Pete Buttigieg.

# Does the soft constraint converge to the rigid constraint?

Dec 01, 2018       11 mins     Tag: modeling computation
tl;nr. No.

# A Decoupling Perspective of Projective Inference in High-dimensional Problems

Oct 10, 2018       4 mins     Tag: modeling
I have recenetly been reading a textbook on decoupling. Decoupling literally means “from dependence to independence”. I initially though the book can help me understand some properties of self-normalized importance sampling, but it turns out...