Normalizing Flows: An Introduction and Review of Current Methods
read the original abstract
Normalizing Flows are generative models which produce tractable distributions where both sampling and density evaluation can be efficient and exact. The goal of this survey article is to give a coherent and comprehensive review of the literature around the construction and use of Normalizing Flows for distribution learning. We aim to provide context and explanation of the models, review current state-of-the-art literature, and identify open questions and promising future directions.
This paper has not been read by Pith yet.
Forward citations
Cited by 6 Pith papers
-
Normalizing flows for density estimation in multi-detector gravitational-wave searches
Normalizing flows replace binned histograms for estimating multi-detector signal parameters in PyCBC, slashing storage by three orders of magnitude with under 0.05% sensitivity loss and up to 6.55% gains in specific cases.
-
Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization
Score-based diffusion models learn the empirical distribution of real LIGO noise to enable unbiased gravitational-wave parameter estimation under only an additivity assumption.
-
Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
Bayesian inference on LVK O1-O3 events with eccentric aligned-spin waveforms yields log10 Bayes factors of 1.77-4.75 favoring eccentricity for GW200129, GW190701 and GW200208_22, and >99.5% probability that at least o...
-
Pulse profile modelling of the 2024 outburst of the accreting millisecond pulsar SRGA J144459.2-604207
Joint NICER+IXPE pulse-profile modeling of SRGA J144459.2-604207 favors large neutron-star mass and radius with two independent hotspots but shows strong sensitivity to joint-analysis methodology.
-
Pre-localization of Massive Black Hole Binaries in the Millihertz Band
A neural spline flow pipeline performs amortized inference on millihertz MBHB signals, delivering ~20 deg² pre-merger sky localizations in ~1 minute while matching PTMCMC sky modes and parameter uncertainties.
-
Constraints on Einstein-aether gravity from the precision timing of PSR J1738+0333
Precision timing of PSR J1738+0333 from EPTA and NANOGrav data yields the tightest strong-field constraints on Einstein-aether parameters from any single binary pulsar.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.