On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

Trend · papers per month

count % of corpus

4 results for “TESS”

Inferring Asteroseismic Parameters from Short Observations Using Deep Learning: Application to TESS and K2 Red Giantsastro-ph.SR

This study uses deep learning to infer stellar parameters from short TESS and K2 observations.

problem Inferring precise stellar parameters from short-duration TESS and K2 observations.

method Developed a machine learning algorithm to infer asteroseismic parameters from one-month-long TESS observations of red giants.

result The algorithm can accurately infer

Δν

and

ν_{\mathrm{max}}

for approximately 50% of TESS samples and

ΔΠ_{1}

for about 200 young red-giants from K2.

Asteroseismology Deep Learning Red Giants TESS K2

2026-05-08abs ↗pdf ↗

Universal Spin Teichmueller Theory, I. The action of P(SL(2,Z)) on Tess^+math.GT

New theory maps spin structures on surfaces, generating key elements.

problem Mapping spin structures on surfaces with finite type.

method Introducing P(SL(2,Z)) and its action on Tess^+.

result Three combinatorial elements generate P(SL(2,Z)).

spin structures Teichmüller theory finite-type surfaces SL(2 Z)

2023-09-24abs ↗pdf ↗

Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series Transformerastro-ph.IM

Transformer model removes noise from light curves efficiently.

problem Challenges in processing astrophysical light curves due to noise.

method Denoising Time Series Transformer (DTST) model trained with masked objective.

result DTST model excels at removing noise and outliers in time series datasets.

Transformer denoising light curves astronomy time series

2022-07-06abs ↗pdf ↗

Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detectionstat.ME

In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention's effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides no mechanism to identify which subpopulations are …

2018-03-24abs ↗pdf ↗