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Our NeurIPS 2024 Publications

Main Track

Feuer, Benjamin; Schirrmeister, Robin Tibor; Cherepanova, Valeriia; Hegde, Chinmay; Hutter, Frank; Goldblum, Micah; Cohen, Niv; White, Colin

TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

Franke, Jörg K. H.; Hefenbrock, Michael; Koehler, Gregor; Hutter, Frank

Improving Deep Learning Optimization through Constrained Parameter Regularization Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

Helli, Kai; Schnurr, David; Hollmann, Noah; Müller, Samuel; Hutter, Frank

Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.

Datasets & Benchmarks Track

Sukthanker, Rhea Sanjay; Zela, Arber; Staffler, Benedikt; Klein, Aaron; Purucker, Lennart; Franke, Joerg K. H.; Hutter, Frank

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models Inproceedings

In: 38th Conference on Neural Information Processing Systems (NeurIPS), DBT Track, 2024.

Workshops

Ferreira, Fabio; Schlageter, Moreno; Rajan, Raghu; Biedenkapp, André; Hutter, Frank

One-shot World Models Using a Transformer Trained on a Synthetic Prior Inproceedings

In: NeurIPS 2024 Workshop on Open-World Agents, 2024.

Küken, Jaris; Purucker, Lennart; Hutter, Frank

Large Language Models Engineer Too Many Simple Features for Tabular Data Inproceedings

In: NeurIPS 2024 Third Table Representation Learning Workshop, 2024, (Oral Presentation).

Arango, Sebastian Pineda; Janowski, Maciej; Purucker, Lennart; Zela, Arber; Hutter, Frank; Grabocka, Josif

Ensembling Finetuned Language Models for Text Classification Inproceedings

In: NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability, 2024.

Mallik, Neeratyoy; Janowski, Maciej; Hog, Johannes; Rakotoarison, Herilalaina; Klein, Aaron; Grabocka, Josif; Hutter, Frank

Warmstarting for Scaling Language Models Inproceedings

In: NeurIPS 2024 Workshop Adaptive Foundation Models, 2024.

Bhethanabhotla, Sathya Kamesh; Swelam, Omar; Siems, Julien; Salinas, David; Hutter, Frank

Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models Inproceedings

In: NeurIPS 2024 TSALM Workshop, 2024, (Spotlight Presentation).

Sukthanker, Rhea Sanjay; Staffler, Benedikt; Hutter, Frank; Klein, Aaron

Large Language Model Compression with Neural Architecture Search Inproceedings

In: NeurIPS 2024 Workshop on Machine Learning and Compression, 2024.

Müller, Andreas; Siems, Julien; Nori, Harsha; Salinas, David; Zela, Arber; Caruana, Rich; Hutter, Frank

GAMformer: Exploring In-Context Learning for Generalized Additive Models Inproceedings

In: NeurIPS 2024 TRL Workshop, 2024.

Hoo, Shi Bin; Müller, Samuel; Salinas, David; Hutter, Frank

The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features Inproceedings

In: NeurIPS 2024 TRL Workshop, 2024.

Grazzi, Riccardo; Siems, Julien; Franke, Jörg K. H.; Zela, Arber; Hutter, Frank; Pontil, Massimiliano

Unlocking State-Tracking in linear RNNs through Negative Eigenvalues Inproceedings

In: NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning Workshop (M3L), 2024, (Oral Presentation).

Strangmann, Tobias; Purucker, Lennart; Franke, Jörg K. H.; Rapant, Ivo; Ferreira, Fabio; Hutter, Frank

Transfer Learning for Finetuning Large Language Models Inproceedings

In: NeurIPS 2024 Workshop on Adaptive Foundation Models, 2024.