Julia Gastinger

According to our database, Julia Gastinger authored at least 9 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs.

Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau

CoRR, 2024

History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting.

Julia Gastinger, Christian Meilicke, Federico Errica, Timo Sztyler, Anett Schülke, Heiner Stuckenschmidt

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

Comparing Apples and Oranges? On the Evaluation of Methods for Temporal Knowledge Graph Forecasting.

Julia Gastinger, Timo Sztyler, Lokesh Sharma, Anett Schuelke, Heiner Stuckenschmidt

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Dynamic Representations of Global Crises: Creation and Analysis of a Temporal Knowledge Graph for Conflicts, Trade and Value Networks.

Julia Gastinger, Nils Steinert, Sabine Gründer-Fahrer, Michael Martin

Proceedings of the Second International Workshop on Linked Data-driven Resilience Research 2023 co-located with Extended Semantic Web Conference 2023 (ESWC 2023), 2023

2022

Human-Centric Research for NLP: Towards a Definition and Guiding Questions.

Bhushan Kotnis, Kiril Gashteovski, Julia Gastinger, Giuseppe Serra, Francesco Alesiani, Timo Sztyler, Ammar Shaker, Na Gong, Carolin Lawrence, Zhao Xu

CoRR, 2022

ProcK: Machine Learning for Knowledge-Intensive Processes.

Tobias Jacobs, Jingyi Yu, Julia Gastinger, Timo Sztyler

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021

A study on Ensemble Learning for Time Series Forecasting and the need for Meta-Learning.

Julia Gastinger, Sébastien Nicolas, Dusica Stepic, Mischa Schmidt, Anett Schülke

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

HAMLET - A Learning Curve-Enabled Multi-Armed Bandit for Algorithm Selection.

Mischa Schmidt, Julia Gastinger, Sebastien Nicolas, Anett Schülke

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

On the Performance of Differential Evolution for Hyperparameter Tuning.

Mischa Schmidt, Shahd Safarani, Julia Gastinger, Tobias Jacobs, Sebastien Nicolas, Anett Schülke

Proceedings of the International Joint Conference on Neural Networks, 2019