4 citations · 11 across the 22 of their papers we have counts for
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TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression
Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Jonas Sonntag +2
Tabular regression is a well-studied problem with numerous industrial applications, yet most existing approaches focus on point estimation, often leading to overconfident predictio…
The Role of Active Learning in Modern Machine Learning
Thorben Werner, Lars Schmidt-Thieme, Vijaya Krishna Yalavarthi
Even though Active Learning (AL) is widely studied, it is rarely applied in contexts outside its own scientific literature. We posit that the reason for this is AL's high computati…
Mixing It Up: Exploring Mixer Networks for Irregular Multivariate Time Series Forecasting
Christian Klötergens, Tim Dernedde, Lars Schmidt-Thieme +1
Forecasting irregularly sampled multivariate time series with missing values (IMTS) is a fundamental challenge in domains such as healthcare, climate science, and biology. While re…
Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time Series Forecasting Based on Biological ODEs
Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz +3
State-of-the-art methods for forecasting irregularly sampled time series with missing values predominantly rely on just four datasets and a few small toy examples for evaluation. W…