most citedMultimodal Deep Learning

10 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ML2024

Variational Approach for Efficient KL Divergence Estimation in Dirichlet Mixture Models

Samyajoy Pal, Christian Heumann

This study tackles the efficient estimation of Kullback-Leibler (KL) Divergence in Dirichlet Mixture Models (DMM), crucial for clustering compositional data. Despite the significan…

cs.CV2023

A tailored Handwritten-Text-Recognition System for Medieval Latin

Philipp Koch, Gilary Vera Nuñez, Esteban Garces Arias +4

The Bavarian Academy of Sciences and Humanities aims to digitize its Medieval Latin Dictionary. This dictionary entails record cards referring to lemmas in medieval Latin, a low-re…

cs.CL2023

Classifying multilingual party manifestos: Domain transfer across country, time, and genre

Matthias Aßenmacher, Nadja Sauter, Christian Heumann

Annotating costs of large corpora are still one of the main bottlenecks in empirical social science research. On the one hand, making use of the capabilities of domain transfer all…

cs.CL2023

How Different Is Stereotypical Bias Across Languages?

Ibrahim Tolga Öztürk, Rostislav Nedelchev, Christian Heumann +4

Recent studies have demonstrated how to assess the stereotypical bias in pre-trained English language models. In this work, we extend this branch of research in multiple different…

stat.ML2023

Using interpretable boosting algorithms for modeling environmental and agricultural data

Fabian Obster, Christian Heumann, Heidi Bohle +1

We describe how interpretable boosting algorithms based on ridge-regularized generalized linear models can be used to analyze high-dimensional environmental data. We illustrate thi…

cs.CL202310 cited

Multimodal Deep Learning

Cem Akkus, Luyang Chu, Vladana Djakovic +14

This book is the result of a seminar in which we reviewed multimodal approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art ap…