相关论文: Data series subtraction with unknown and unmodeled…

Parameter-efficient fine-tuning methods such as LoRA enable practical adaptation of large language models but provide no principled uncertainty estimates, leading to poorly calibrated predictions and unreliable behavior under domain shift.…

This paper discusses force noise in LISA and LISA Pathfinder arising from the interaction of patch potentials on the test mass and surrounding electrode housing surfaces with their own temporal fluctuations. We aim to estimate the…

In this paper, we study a simple correlation-based strategy for estimating the unknown delay and amplitude of a signal based on a small number of noisy, randomly chosen frequency-domain samples. We model the output of this "compressive…

Image subtraction in astronomy is a tool for transient object discovery and characterization, particularly useful in wide fields, and is well suited for moving or photometrically varying objects such as asteroids, extra-solar planets and…

To achieve the sensitivity required to detect signals from neutral hydrogen from the Cosmic Dawn and Epoch of Reionisation it is critical to have a well-calibrated instrument which has a stable calibration over the course of the…

Tilt-to-length coupling was the limiting noise source in LISA Pathfinder between 20 and 200 mHz before subtraction in post-processing. To prevent the adding of sensing noise to the data by the subtraction process, the success of this…

The space-based gravitational-wave observatory LISA relies on a form of synthetic interferometry (time-delay interferometry, or TDI) where the otherwise overwhelming laser phase noise is canceled by linear combinations of appropriately…

The high energy physics unfolding problem is an important statistical inverse problem in data analysis at the Large Hadron Collider (LHC) at CERN. The goal of unfolding is to make nonparametric inferences about a particle spectrum from…

Air pollution, especially particulate matter 2.5 (PM2.5), is a pressing concern for public health and is difficult to estimate in developing countries (data-poor regions) due to a lack of ground sensors. Transfer learning models can be…

Spatial frequency estimation from a mixture of noisy sinusoids finds applications in various fields. While subspace-based methods offer cost-effective super-resolution parameter estimation, they demand precise array calibration, posing…

Laser Interferometer Space Antenna LISA represents the next frontier in gravitationalwave GW astronomy targeting the detection of millihertz gravitational signals Central to LISAs operation is the nanosecondprecision estimation of the light…

We present a noise estimation and subtraction algorithm capable of increasing the sensitivity of heterodyne laser interferometers by one order of magnitude. The heterodyne interferometer is specially designed for dynamic measurements of a…

Variations in the instrumental noise of the Laser Interferometer Space Antenna (LISA) over time are expected as a result of e.g. scheduled satellite operations or unscheduled glitches. We demonstrate that these fluctuations can be leveraged…

Extreme-mass-ratio-inspiral observations from future space-based gravitational-wave detectors such as LISA will enable strong-field tests of general relativity with unprecedented precision, but at prohibitive computational cost if existing…

Laser Interferometer Space Antenna (LISA) observations of massive black hole binaries (MBHBs) will provide long duration inspiral signals with high signal-to-noise ratio (SNR) data, ideal for testing general relativity (GR) in the…

Integral field spectroscopy (IFS) provides spatially resolved spectra, enabling detailed studies that address the physical and kinematic properties of the interstellar medium. A critical step in analyzing IFS data is the decomposition of…

Future drag-free missions for space-based experiments in gravitational physics require a Gravitational Reference Sensor with extremely demanding sensing and disturbance reduction requirements. A configuration with two cubical sensors is the…

First-shot (FS) unsupervised anomalous sound detection (ASD) is a brand-new task introduced in DCASE 2023 Challenge Task 2, where the anomalous sounds for the target machine types are unseen in training. Existing methods often rely on the…

We assume a spatial blind source separation model in which the observed multivariate spatial data is a linear mixture of latent spatially uncorrelated Gaussian random fields containing a number of pure white noise components. We propose a…

We introduce a novel framework for upsampled Point Spread Function (PSF) modeling using pixel-level Bayesian inference. Accurate PSF characterization is critical for precision measurements in many fields including: weak lensing, astrometry,…