1 citations · 3 across the 14 of their papers we have counts for
9 papers · 1 filter
Do Tabular Foundation Models Agree with Themselves?
Christian Klötergens, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme +1
Tabular Foundation Models (TFMs) are currently the best approach to tabular prediction problems. They are constructed as transformers that approximate the Bayesian posterior predic…
The Importance of Encoder Choice:A Tabular-Image Study
Ilia Koloiarov, Diego Coello de Portugal Mecke, Vijaya Krishna Yalavarthi +2
Multimodal learning usually requires a dedicated encoder per modality. When a tabular modality is involved, prior work has been mostly using a \emph{plain MLP} as the encoder. Yet…
Valid and Expressive Copulas for Irregular Multivariate Time Series
Christian Klötergens, Tom Hanika, Lars Schmidt-Thieme +1
We introduce CopFITi, a copula model for probabilistic forecasting of irregular multivariate time series (IMTS). Our model combines the expressivity of normalizing flows for univar…
Prune, Update and Trim: Robust Structured Pruning for Large Language Models
Diego Coello de Portugal Mecke, Tom Hanika, Lars Schmidt-Thieme
Large Language Models (LLMs) have experienced significant growth and development in recent years. However, performing inference on LLMs remains costly, especially for long-context…
LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification
Ahmad Bdeir, Johannes Burchert, Tom Hanika +2
Electroencephalogram (EEG) classification plays a key role in medical diagnosis and brain-computer interfaces, but remains challenging due to low signal-to-noise ratios and high in…
What is the dimension of your binary data? -- and how to compute it quickly
Tom Hanika, Tobias Hille
Dimensionality is an important aspect for analyzing and understanding (high-dimensional) data. In their 2006 ICDM paper Tatti et al. answered the question for a (interpretable) dim…