Publications

Tomislav Đuričić, Peter Müllner, Nicole Weidinger, Neven ElSayed, Dominik Kowald, Eduardo Veas (2024). AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. ECAI'24.

PDF Cite Project Video DOI

Tomislav Đuričić, Dominik Kowald, Emanuel Lacić, Elisabeth Lex (2023). Beyond-Accuracy: A Review on Diversity, Serendipity, and Fairness in Recommender Systems Based on Graph Neural Networks. Front. Big Data.

PDF Cite Project DOI

Emanuel Lacić, Tomislav Đuričić, Leon Fadljević, Dieter Theiler, Dominik Kowald (2023). Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings. ECIR'23.

PDF Cite Project DOI

Mario Lovrić, Tomislav Đuričić, Hussain Hussain, Bono Lucić, Roman Kern (2023). PyChemFlow: an automated pre-processing pipeline in Python for reproducible machine learning on chemical data. ChemRxiv.

PDF Cite DOI

Tomislav Đuričić, Dominik Kowald, Markus Schedl, Elisabeth Lex (2022). My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music. ASONAM'21.

PDF Cite Project DOI

Hussain Hussain, Tomislav Đuričić, Elisabeth Lex, Denis Helić, Roman Kern (2021). The interplay between communities and homophily in semi-supervised classification using graph neural networks. Appl. Netw. Sci.

PDF Cite Project DOI

Oana Inel, Tomislav Đuričić, Harmanpreet Kaur, Elisabeth Lex, Nava Tintarev (2021). Design Implications for Explanations: A Case Study on Supporting Reflective Assessment of Potentially Misleading Videos. Front. Artif. Intell.

PDF Cite Project DOI

Hussain Hussain, Tomislav Đuričić, Elisabeth Lex, Denis Helić, Markus Strohmaier, Roman Kern (2021). Structack: Structure-based Adversarial Attacks on Graph Neural Networks. HT'21.

PDF Cite Project DOI

Mario Lovrić, Tomislav Đuričić, Han T.N. Tran, Hussain Hussain, Emanuel Lacić, Morten A. Rasmussen, Roman Kern (2021). Should We Embed in Chemistry? A Comparison of Unsupervised Transfer Learning with PCA, UMAP, and VAE on Molecular Fingerprints. Pharmaceuticals (MDPI).

PDF Cite Project DOI

Tomislav Đuričić, Volker Seiser, Elisabeth Lex (2021). Cross-platform analysis of user comments in YouTube videos linked on Reddit’s conspiracy theory forum. IC2S2'21.

PDF Cite Project DOI

Hussain Hussain, Tomislav Đuričić, Elisabeth Lex, Roman Kern, Denis Helić (2021). On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks. CompleNet'20.

PDF Cite Project DOI

Tomislav Đuričić, Hussain Hussain, Emanuel Lacić, Dominik Kowald, Denis Helić, Elisabeth Lex (2020). Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering. ISMIS'20.

PDF Cite Project DOI

Emanuel Lacić, Markus Reiter-Haas, Tomislav Đuričić, Valentin Slawicek, Elisabeth Lex (2019). Should we embed? A study on the online performance of utilizing embeddings for real-time job recommendations. RecSys'19.

PDF Cite Project DOI

Tomislav Đuričić, Emanuel Lacić, Dominik Kowald, Elisabeth Lex (2019). Exploiting weak ties in trust-based recommender systems using regular equivalence. EURO CSS'19.

PDF Cite DOI

Tomislav Đuričić, Emanuel Lacić, Dominik Kowald, Elisabeth Lex (2018). Trust-based collaborative filtering: tackling the cold start problem using regular equivalence. RecSys'18.

PDF Cite DOI

Emanuel Lacić, Matthias Traub, Tomislav Đuričić, Eva Haslauer, Elisabeth Lex (2018). Gone in 30 days! Predictions for car import planning. it - Information Technology.

PDF Cite Project DOI