Trending Research
Conformal prediction beyond exchangeability
salesforce/online_conformal
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Our new methods are provably robust, with substantially less loss of coverage when exchangeability is violated due to distribution drift or other challenging features of real data, while also achieving the same coverage guarantees as existing conformal prediction methods if the data points are in fact exchangeable.
Methodology
Bambi: A simple interface for fitting Bayesian linear models in Python
The popularity of Bayesian statistical methods has increased dramatically in recent years across many research areas and industrial applications.
Computation
Tutorial: Effective visual communication for the quantitative scientist
With this competency, we can better understand data and influence decisions towards appropriate actions.
Applications
ruptures: change point detection in Python
ruptures is a Python library for offline change point detection.
Computation Mathematical Software
Beating the bookies with their own numbers - and how the online sports betting market is rigged
The online sports gambling industry employs teams of data analysts to build forecast models that turn the odds at sports games in their favour.
Applications Other Computer Science Other Statistics
Probabilistic Programming in Python using PyMC
pymc-devs/pymc3
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Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code.
Computation
Bayesian Workflow
zhaoolee/garss
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The Bayesian approach to data analysis provides a powerful way to handle uncertainty in all observations, model parameters, and model structure using probability theory.
Methodology
A flexible forecasting model for production systems
This paper discusses desirable properties of forecasting models in production systems.
Methodology
Estimating Treatment Effects with Causal Forests: An Application
We apply causal forests to a dataset derived from the National Study of Learning Mindsets, and consider resulting practical and conceptual challenges.
Methodology
StateSpaceModels.jl: a Julia Package for Time-Series Analysis in a State-Space Framework
StateSpaceModels. jl is an open-source Julia package for modeling, forecasting and simulating time series in a state-space framework.
Computation Optimization and Control
