Arik Reuter

According to our database, Arik Reuter authored at least 15 papers between 2023 and 2026.

Collaborative distances:

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

2026

Use What You Know: Causal Foundation Models with Partial Graphs.

Arik Reuter, Anish Dhir, Cristiana Diaconu, Jake Robertson, Ole Ossen, Frank Hutter, Adrian Weller, Mark van der Wilk, Bernhard Schölkopf

CoRR, February, 2026

2025

Probabilistic Topic Modeling With Transformer Representations.

Arik Reuter, Anton Thielmann, Christoph Weisser, Benjamin Säfken, Thomas Kneib

IEEE Trans. Neural Networks Learn. Syst., August, 2025

Beyond Black-Box Predictions: Identifying Marginal Feature Effects in Tabular Transformer Networks.

Anton Thielmann, Arik Reuter, Benjamin Säfken

CoRR, April, 2025

Do-PFN: In-Context Learning for Causal Effect Estimation.

Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Can Transformers Learn Full Bayesian Inference in Context?

Arik Reuter, Tim G. J. Rudner, Vincent Fortuin, David Rügamer

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Position: The Future of Bayesian Prediction Is Prior-Fitted.

Samuel Müller, Arik Reuter, Noah Hollmann, David Rügamer, Frank Hutter

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Interpretable Additive Tabular Transformer Networks.

Anton Frederik Thielmann, Arik Reuter, Thomas Kneib, David Rügamer, Benjamin Säfken

Trans. Mach. Learn. Res., 2024

Mambular: A Sequential Model for Tabular Deep Learning.

Anton Frederik Thielmann, Manish Kumar, Christoph Weisser, Arik Reuter, Benjamin Säfken, Soheila Samiee

CoRR, 2024

Neural Additive Image Model: Interpretation through Interpolation.

Arik Reuter, Anton Thielmann, Benjamin Säfken

CoRR, 2024

Probabilistic Topic Modelling with Transformer Representations.

Arik Reuter, Anton Thielmann, Christoph Weisser, Benjamin Säfken, Thomas Kneib

CoRR, 2024

GPTopic: Dynamic and Interactive Topic Representations.

Arik Reuter, Anton Thielmann, Christoph Weisser, Sebastian Fischer, Benjamin Säfken

CoRR, 2024

Topics in the Haystack: Enhancing Topic Quality through Corpus Expansion.

Anton Thielmann, Arik Reuter, Quentin Seifert, Elisabeth Bergherr, Benjamin Säfken

Comput. Linguistics, 2024

STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module.

Anton Thielmann, Arik Reuter, Christoph Weisser, Gillian Kant, Manish Kumar, Benjamin Säfken

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2024

2023

Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data.

Christoph Weisser, Christoph Gerloff, Anton Thielmann, Andre Python, Arik Reuter, Thomas Kneib, Benjamin Säfken

Comput. Stat., June, 2023

Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence.

Anton Thielmann, Quentin Seifert, Arik Reuter, Elisabeth Bergherr, Benjamin Säfken

CoRR, 2023