Lifeboat Foundation

The bold new idea could offer an alternate explanation for cosmic expansion.

See what your furniture might look like from every angle.

Users of Photoshop, Substance 3D, and other Adobe products are now required to provide the company with unlimited access to their creations.

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.

Instructor:

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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.

Patreon: https://www.patreon.com/seanmcarrollBlog post with audio player, show notes, and transcript: https://www.preposterousuniverse.com/podcast/2024/06/03…

And the implications are enormous.

Nvidia stock has surged by more than 700% since the start of last year, boosting CEO Jensen Huang’s wealth by about $93 billion.

From Google Research.

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.

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