Related papers: Reliability Correction is Key for Robust Kepler Oc…
A fundamental challenge in machine learning is the choice of a loss as it characterizes our learning task, is minimized in the training phase, and serves as an evaluation criterion for estimators. Proper losses are commonly chosen, ensuring…
Conformal prediction (CP) converts any model's output to prediction sets with a guarantee to cover the true label with (adjustable) high probability. Robust CP extends this guarantee to worst-case (adversarial) inputs. Existing baselines…
We consider error correction in quantum key distribution. To avoid that Alice and Bob unwittingly end up with different keys precautions must be taken. Before running the error correction protocol, Bob and Alice normally sacrifice some bits…
For any black-box model, conformal prediction (CP) returns prediction sets guaranteed to include the true label with high adjustable probability. Robust CP (RCP) extends the guarantee to the worst case noise up to a pre-defined magnitude.…
We investigate potential biases in the measurements of exoplanet orbital parameters obtained from radial velocity observations for single-planet systems. We create a mock catalog of radial velocity data, choosing input planet masses,…
Probabilistic classifiers are central for making informed decisions under uncertainty. Based on the maximum expected utility principle, optimal decision rules can be derived using the posterior class probabilities and misclassification…
We describe a new metric that uses machine learning to determine if a periodic signal found in a photometric time series appears to be shaped like the signature of a transiting exoplanet. This metric uses dimensionality reduction and…
Causal discovery from observational data is an important tool in many branches of science. Under certain assumptions it allows scientists to explain phenomena, predict, and make decisions. In the large sample limit, sound and complete…
Aims. We study a subset of the planetary population characterized both by HARPS and Kepler surveys. We compare the statistical properties of planets in systems with m.sin i >5-10 M_Earth and R>2 R_Earth. If we assume that the underlying…
In sequential search, alternatives are tested until the true class is found. Standard proper scoring rules like log loss are local, ignoring the ranking of competitors and misaligning model evaluation with search utility. We show that…
Exoplanet surveys like Kepler, TESS, and K2 have shown that planetary systems are common in our galaxy. These surveys, along with several others, have identified thousands of planetary candidates, with more than five thousand having already…
This study presents a comprehensive evaluation of various classification algorithms used for the detection of exoplanets using labeled time series data from the Kepler mission. The study investigates the performance of six commonly employed…
The role of radial velocity (RV) jitter in extrasolar planet search surveys is discussed. Based on the maximum likelihood principle, improved statistical algorithms for RV fitting and period search are developed. These algorithms…
The recently approved NASA K2 mission has the potential to multiply by an order of magnitude the number of short-period transiting planets found by Kepler around bright and low-mass stars, and to revolutionise our understanding of stellar…
We investigate the distributions of the orbital period ratios of adjacent planets in high multiplicity \kepler\ systems (four or more planets) and low multiplicity systems (two planets). Modeling the low multiplicity sample as essentially…
We describe a technique for solving for the orbital elements of multiple planets from radial velocity (RV) and/or astrometric data taken with 1 m/s and microarcsecond precision, appropriate for efforts to detect Earth-massed planets in…
A long noted difficulty when assessing the reliability (or calibration) of forecasting systems is that reliability, in general, is a hypothesis not about a finite dimensional parameter but about an entire functional relationship. A…
Stellar radial velocity (RV) measurements have proven to be a very successful method for detecting extrasolar planets. Analysing RV data to determine the parameters of the extrasolar planets is a significant statistical challenge owing to…
Modern applications of conformal inference to multiple testing problems, such as outlier detection and candidate selection, often involve selecting test samples whose conformal p-values fall below a threshold. The quality of such methods is…
In many real-world binary classification tasks (e.g. detection of certain objects from images), an available dataset is imbalanced, i.e., it has much less representatives of a one class (a minor class), than of another. Generally, accurate…