Lukas Galke | DeepAI

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Featured Co-authors

Ansgar Scherp
27 publications
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Yoav Ram
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Bhakti Khera
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∙ 02/23/2023

What makes a language easy to deep-learn?

Neural networks drive the success of natural language processing. A fund...

0 Lukas Galke, et al. ∙

∙ 04/22/2022

Emergent Communication for Understanding Human Language Evolution: What's Missing?

Emergent communication protocols among humans and artificial neural netw...

2 Lukas Galke, et al. ∙

∙ 04/08/2022

Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single- and Multi-Label Text Classification

Graph neural networks have triggered a resurgence of graph-based text cl...

7 Andor Diera, et al. ∙

∙ 12/20/2021

Lifelong Learning in Evolving Graphs with Limited Labeled Data and Unseen Class Detection

Large-scale graph data in the real-world are often dynamic rather than s...

41 Lukas Galke, et al. ∙

∙ 09/17/2021

New Students on Sesame Street: What Order-Aware Matrix Embeddings Can Learn from BERT

Large-scale pretrained language models (PreLMs) are revolutionizing natu...

0 Lukas Galke, et al. ∙

∙ 09/08/2021

Forget me not: A Gentle Reminder to Mind the Simple Multi-Layer Perceptron Baseline for Text Classification

Graph neural networks have triggered a resurgence of graph-based text cl...

0 Lukas Galke, et al. ∙

∙ 05/10/2021

Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities

We address the problem of recommending relevant items to a user in order...

0 Iacopo Vagliano, et al. ∙

∙ 06/25/2020

Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift

Current graph neural networks (GNNs) are promising, especially when the ...

0 Lukas Galke, et al. ∙

∙ 07/22/2019

Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels

We present multi-modal adversarial autoencoders for recommendation and e...

0 Lukas Galke, et al. ∙

∙ 05/15/2019

Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference

Large-scale graph data in real-world applications is often not static bu...

0 Lukas Galke, et al. ∙

∙ 02/18/2019

CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model

Continuous Bag of Words (CBOW) is a powerful text embedding method. Due ...

0 Florian Mai, et al. ∙

∙ 01/20/2018

Using Deep Learning For Title-Based Semantic Subject Indexing To Reach Competitive Performance to Full-Text

For (semi-)automated subject indexing systems in digital libraries, it i...

0 Florian Mai, et al. ∙

∙ 05/15/2017

Using Titles vs. Full-text as Source for Automated Semantic Document Annotation

A significant part of the largest Knowledge Graph today, the Linked Open...

0 Lukas Galke, et al. ∙

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