Ian Langmore
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View article: NeuralGCM precipitation checkpoints
NeuralGCM precipitation checkpoints Open
Model checkpoints for NeuralGCM. See the NeuralGCM documentation for usage instructions.
View article: Neural general circulation models for weather and climate
Neural general circulation models for weather and climate Open
General circulation models (GCMs) are the foundation of weather and climate prediction 1,2 . GCMs are physics-based simulators that combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes su…
View article: WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models
WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models Open
WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting benchmark proposed by (Rasp et al., 2020, https://doi.org/10.1029/2020ms002203 ), designed with the aim to accelerate progress in data‐driven weather m…
View article: A scalable system to measure contrail formation on a per-flight basis
A scalable system to measure contrail formation on a per-flight basis Open
Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from satellite data whether a flight has made a persistent contr…
View article: Neural General Circulation Models for Weather and Climate
Neural General Circulation Models for Weather and Climate Open
General circulation models (GCMs) are the foundation of weather and climate prediction. GCMs are physics-based simulators which combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes such a…
View article: WeatherBench 2: A benchmark for the next generation of data-driven global weather models
WeatherBench 2: A benchmark for the next generation of data-driven global weather models Open
WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an op…
View article: A scalable system to measure contrail formation on a per-flight basis
A scalable system to measure contrail formation on a per-flight basis Open
Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from satellite data whether a flight has made a persistent contr…
View article: HAMILTONIAN MONTE CARLO IN INVERSE PROBLEMS. ILL-CONDITIONING AND MULTIMODALITY
HAMILTONIAN MONTE CARLO IN INVERSE PROBLEMS. ILL-CONDITIONING AND MULTIMODALITY Open
The Hamiltonian Monte Carlo (HMC) method allows sampling from continuous densities. Favorable scaling with dimension has led to wide adoption of HMC by the statistics community. Modern autodifferentiating software should allow more widespr…
View article: Hamiltonian Monte Carlo in Inverse Problems; Ill-Conditioning and Multi-Modality
Hamiltonian Monte Carlo in Inverse Problems; Ill-Conditioning and Multi-Modality Open
The Hamiltonian Monte Carlo (HMC) method allows sampling from continuous densities. Favorable scaling with dimension has led to wide adoption of HMC by the statistics community. Modern auto-differentiating software should allow more widesp…
View article: tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware
tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware Open
Markov chain Monte Carlo (MCMC) is widely regarded as one of the most important algorithms of the 20th century. Its guarantees of asymptotic convergence, stability, and estimator-variance bounds using only unnormalized probability function…
View article: Constructing High Precision Knowledge Bases with Subjective and Factual Attributes
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes Open
Knowledge bases (KBs) are the backbone of many ubiquitous applications and are thus required to exhibit high precision. However, for KBs that store subjective attributes of entities, e.g., whether a movie is "kid friendly", simply estimati…
View article: Constructing High Precision Knowledge Bases with Subjective and Factual\n Attributes
Constructing High Precision Knowledge Bases with Subjective and Factual\n Attributes Open
Knowledge bases (KBs) are the backbone of many ubiquitous applications and\nare thus required to exhibit high precision. However, for KBs that store\nsubjective attributes of entities, e.g., whether a movie is "kid friendly",\nsimply estim…
View article: A Condition Number for Hamiltonian Monte Carlo
A Condition Number for Hamiltonian Monte Carlo Open
Hamiltonian Monte Carlo is a popular sampling technique for smooth target densities. The scale lengths of the target have long been known to influence integration error and sampling efficiency. However, quantitative measures intrinsic to t…
View article: NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Open
Hamiltonian Monte Carlo is a powerful algorithm for sampling from difficult-to-normalize posterior distributions. However, when the geometry of the posterior is unfavorable, it may take many expensive evaluations of the target distribution…
View article: Quadrature Compound: An approximating family of distributions
Quadrature Compound: An approximating family of distributions Open
Compound distributions allow construction of a rich set of distributions. Typically they involve an intractable integral. Here we use a quadrature approximation to that integral to define the quadrature compound family. Special care is tak…
View article: TensorFlow Distributions
TensorFlow Distributions Open
The TensorFlow Distributions library implements a vision of probability theory adapted to the modern deep-learning paradigm of end-to-end differentiable computation. Building on two basic abstractions, it offers flexible building blocks fo…
View article: statsmodels: "Version 0.7.0 Release Candidate 1"
statsmodels: "Version 0.7.0 Release Candidate 1" Open
Statsmodels: statistical modeling and econometrics in Python