Noah Hollmann - RankMe

21 papers A* 6Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accurate predictions on small data with a tabular foundation model. Nat. Noah Hollmann, Samuel Müller, Lennart Purucker, Arjun Krishnakumar, Max Körfer, Shi Bin Hoo, Robin Tibor Schirrmeister, Frank Hutter
2025	J	`jnl`	Do-PFN: In-Context Learning for Causal Effect Estimation. CoRR Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf
2025	A*	`conf`	FairPFN: A Tabular Foundation Model for Causal Fairness. ICML Jake Robertson, Noah Hollmann, Samuel Müller, Noor H. Awad, Frank Hutter
2025	J	`jnl`	FairPFN: A Tabular Foundation Model for Causal Fairness. CoRR Jake Robertson, Noah Hollmann, Samuel Müller, Noor H. Awad, Frank Hutter
2025	—	`conf`	Position: The Future of Bayesian Prediction Is Prior-Fitted. ICML (Position Papers) Samuel Müller, Arik Reuter, Noah Hollmann, David Rügamer, Frank Hutter
2025	J	`jnl`	Position: The Future of Bayesian Prediction Is Prior-Fitted. CoRR Samuel Müller, Arik Reuter, Noah Hollmann, David Rügamer, Frank Hutter
2025	J	`jnl`	Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data. CoRR Anurag Garg, Muhammad Ali, Noah Hollmann, Lennart Purucker, Samuel Müller, Frank Hutter
2025	J	`jnl`	TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models. CoRR Léo Grinsztajn, Klemens Flöge, Oscar Key, Felix Birkel, Philipp Jund, Brendan Roof, Benjamin Jäger, Dominik Safaric, Simone Alessi, Adrian Hayler, Mihir Manium, Rosen Yu, Felix Jablonski, Shi Bin Hoo, Anurag Garg, Jake Robertson, Magnus Bühler, Vladyslav Moroshan, Lennart Purucker, Clara Cornu, Lilly Charlotte Wehrhahn, Alessandro Bonetto, Bernhard Schölkopf, Sauraj Gambhir, Noah Hollmann, Frank Hutter
2024	J	`jnl`	Bayes' Power for Explaining In-Context Learning Generalizations. CoRR Samuel Müller, Noah Hollmann, Frank Hutter
2024	A*	`conf`	Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data. NeurIPS Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter
2024	J	`jnl`	Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data. CoRR Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter
2024	J	`jnl`	FairPFN: Transformers Can do Counterfactual Fairness. CoRR Jake Robertson, Noah Hollmann, Noor H. Awad, Frank Hutter
2023	J	`jnl`	LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering. CoRR Noah Hollmann, Samuel Müller, Frank Hutter
2023	A*	`conf`	Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering. NeurIPS Noah Hollmann, Samuel Müller, Frank Hutter
2023	J	`jnl`	PFNs Are Flexible Models for Real-World Bayesian Optimization. CoRR Samuel Müller, Matthias Feurer, Noah Hollmann, Frank Hutter
2023	A*	`conf`	PFNs4BO: In-Context Learning for Bayesian Optimization. ICML Samuel Müller, Matthias Feurer, Noah Hollmann, Frank Hutter
2023	A*	`conf`	TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second. ICLR Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter
2022	J	`jnl`	Meta-Learning a Real-Time Tabular AutoML Method For Small Data. CoRR Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter
2022	A*	`conf`	Transformers Can Do Bayesian Inference. ICLR Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter
2021	J	`jnl`	Transformers Can Do Bayesian Inference. CoRR Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter
2017	—	`conf`	Ranking and Feedback-based Stopping for Recall-Centric Document Retrieval. CLEF (Working Notes) Noah Hollmann, Carsten Eickhoff