Presents a practical fully time-domain end-to-end likelihood for gravitational-wave inference with structured linear algebra and GPU acceleration.
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5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 5verdicts
UNVERDICTED 5representative citing papers
An E(3)-equivariant graph neural network trained on MAGNDATA experimental structures predicts magnetic orders using a new primitive modulated structure representation that handles commensurate and incommensurate cases uniformly.
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
Waveform modeling uncertainties can distort features in the binary black hole mass distribution inferred from gravitational-wave data more than statistical uncertainties.
Upper bounds on the dark matter fraction in MACHOs of 10^3 to 10^7 solar masses are derived from limits on distortions to the global 21-cm signal at z~17, z~89, and z>300.
citing papers explorer
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Accelerated Time-domain Analysis for Gravitational Wave Astronomy
Presents a practical fully time-domain end-to-end likelihood for gravitational-wave inference with structured linear algebra and GPU acceleration.
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Universal Magnetic Structure Prediction from Atomic Coordinates with Near-Experimental Accuracy
An E(3)-equivariant graph neural network trained on MAGNDATA experimental structures predicts magnetic orders using a new primitive modulated structure representation that handles commensurate and incommensurate cases uniformly.
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Posterior Predictive Checks for Gravitational-wave Populations: Limitations and Improvements
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
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Is the Binary Black Hole Population Inference from Gravitational-Wave Data Robust?
Waveform modeling uncertainties can distort features in the binary black hole mass distribution inferred from gravitational-wave data more than statistical uncertainties.
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Dark ages bounds on non-accreting massive compact halo objects
Upper bounds on the dark matter fraction in MACHOs of 10^3 to 10^7 solar masses are derived from limits on distortions to the global 21-cm signal at z~17, z~89, and z>300.