This tutorial aims to provide a survey of the Bayesian perspective of causal inference under the potential outcomes framework. We review the causal estimands, assignment mechanism, the general structure of Bayesian inference of causal effects, and sensitivity analysis. We highlight issues that are unique to Bayesian causal inference, including the role of the propensity score, the definition of identifiability, the choice of priors in both low and high dimensional regimes. We point out the central role of covariate overlap and more generally the design stage in Bayesian causal inference. We extend the discussion to two complex assignment mechanisms: instrumental variable and time-varying treatments. We identify the strengths and weaknesses of the Bayesian approach to causal inference. Throughout, we illustrate the key concepts via examples.
We propose and demonstrate the first chip-based 3D printer, consisting of a silicon-photonics chip that emits non-mechanically-reconfigurable beams into photocurable resin, enabling future compact, portable, and low-cost next-generation 3D printers.
Item-Language Model for Conversational Recommendation.
Large-language Models (LLMs) have been extremely successful at tasks like complex dialogue understanding, reasoning and coding due to their emergent abilities.
The widely held view that sperm counts in men are dropping around the world may be wrong, according to a new study by University of Manchester, Queen’s University in Kingston, Canada and Cryos International, Denmark.
In a development at the intersection of quantum mechanics and general relativity, researchers have made significant strides toward unraveling the mysteries of quantum gravity. This work sheds new light on future experiments that hold promise for resolving one of the most fundamental enigmas in modern physics: the reconciliation of Einstein’s theory of gravity with the principles of quantum mechanics.
Rising costs of living and education have presented unique challenges for Gen Z. NYU Professor of Marketing Scott Galloway describes the inequities in opportunity and education young people face, while offering possible solutions. #Education #GenZ #WSJ