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Papers

TabPFN Followups

Forecastpfn: Synthetically-trained zero-shot forecasting Dooley, Khurana, Mohapatra, Naidu, White
Advances in Neural Information Processing Systems, 2024, Volume 36.

Interpretable machine learning for TabPFN Rundel, Kobialka, von Crailsheim, Feurer, Nagler, R{"u}gamer
World Conference on Explainable Artificial Intelligence, 2024, Pages 465--476.

Scaling tabpfn: Sketching and feature selection for tabular prior-data fitted networks Feuer, Hegde, Cohen
arXiv preprint arXiv:2311.10609, 2023.

In-Context Data Distillation with TabPFN Ma, Thomas, Yu, Caterini
arXiv preprint arXiv:2402.06971, 2024.

Tokenize features, enhancing tables: the FT-TABPFN model for tabular classification Liu, Yang, Liang, Pang, Zou
arXiv preprint arXiv:2406.06891, 2024.

Towards Localization via Data Embedding for TabPFN Koshil, Nagler, Feurer, Eggensperger
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

Enhancing Classification Performance Through the Synergistic Use of XGBoost, TABPFN, and LGBM Models Prabowo, others
2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), 2023, Pages 255--259.

The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features Hoo, M{"u}ller, Salinas, Hutter
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

TabPFGen--Tabular Data Generation with TabPFN Ma, Dankar, Stein, Yu, Caterini
arXiv preprint arXiv:2406.05216, 2024.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Helli, Schnurr, Hollmann, M{"u}ller, Hutter
arXiv preprint arXiv:2411.10634, 2024.

TabFlex: Scaling Tabular Learning to Millions with Linear Attention Zeng, Kang, Mueller
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

Retrieval \& Fine-Tuning for In-Context Tabular Models Thomas, Ma, Hosseinzadeh, Golestan, Yu, Volkovs, Caterini
arXiv preprint arXiv:2406.05207, 2024.

TabDPT: Scaling Tabular Foundation Models Ma, Thomas, Hosseinzadeh, Kamkari, Labach, Cresswell, Golestan, Yu, Volkovs, Caterini
arXiv preprint arXiv:2410.18164, 2024.

Why In-Context Learning Transformers are Tabular Data Classifiers Breejen, Bae, Cha, Yun
arXiv preprint arXiv:2405.13396, 2024.

MotherNet: Fast Training and Inference via Hyper-Network Transformers Mueller, Curino, Ramakrishnan
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

Mixture of In-Context Prompters for Tabular PFNs Xu, Cirit, Asadi, Sun, Wang
arXiv preprint arXiv:2405.16156, 2024.

Fast and Accurate Zero-Training Classification for Tabular Engineering Data Picard, Ahmed
arXiv preprint arXiv:2401.06948, 2024.

Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning den Breejen, Bae, Cha, Kim, Koh, Yun
NeurIPS 2023 Second Table Representation Learning Workshop, 2023.

TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks Feuer, Schirrmeister, Cherepanova, Hegde, Hutter, Goldblum, Cohen, White
arXiv preprint arXiv:2402.11137, 2024.

Exploration of autoregressive models for in-context learning on tabular data Baur, Kim
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting Margeloiu, Bazaga, Simidjievski, Li{`o}, Jamnik
arXiv preprint arXiv:2406.01805, 2024.

Large Scale Transfer Learning for Tabular Data via Language Modeling Gardner, Perdomo, Schmidt
arXiv preprint arXiv:2406.12031, 2024.

AnnotatedTables: A Large Tabular Dataset with Language Model Annotations Hu, Fountalis, Tian, Vasiloglou
arXiv preprint arXiv:2406.16349, 2024.

TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling Gorishniy, Kotelnikov, Babenko
arXiv preprint arXiv:2410.24210, 2024.

Pre-Trained Tabular Transformer for Real-Time, Efficient, Stable Radiomics Data Processing: A Comprehensive Study Jiang, Jia, Zhang, Li
2023 IEEE International Conference on E-health Networking, Application \& Services (Healthcom), 2023, Pages 276--281.

TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models Margeloiu, Jiang, Simidjievski, Jamnik
arXiv preprint arXiv:2409.16118, 2024.

Augmenting Small-size Tabular Data with Class-Specific Energy-Based Models Margeloiu, Jiang, Simidjievski, Jamnik
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

FORECASTPFN: ZERO-SHOT LOW-RESOURCE FORECASTING Khurana, Dooley, Naidu, White, AI
No Source, No Year.

What exactly has TabPFN learned to do? McCarter
The Third Blogpost Track at ICLR 2024, No Year.

Statistical foundations of prior-data fitted networks Nagler
International Conference on Machine Learning, 2023, Pages 25660--25676.

Why In-Context Learning Transformers are Tabular Data Classifiers den Breejen, Bae, Cha, Yun
arXiv e-prints, 2024, Pages arXiv--2405.

TabPFN Application

Large-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells Offensperger, Tin, Duran-Frigola, Hahn, Dobner, Ende, Strohbach, Rukavina, Brennsteiner, Ogilvie, others
Science, 2024, Volume 384, Issue 6694, Pages eadk5864.

Deep learning for cross-selling health insurance classification Chu, Than, Jo
2024 International Conference on Green Energy, Computing and Sustainable Technology (GECOST), 2024, Pages 453--457.

Early fault classification in rotating machinery with limited data using TabPFN Magad{'a}n, Rold{'a}n-G{'o}mez, Granda, Su{'a}rez
IEEE Sensors Journal, 2023.

Artificial intelligence-driven predictive framework for early detection of still birth Alzakari, Aldrees, Umer, Cascone, Innab, Ashraf
SLAS technology, 2024, Volume 29, Issue 6, Pages 100203.

Prostate Cancer Diagnosis via Visual Representation of Tabular Data and Deep Transfer Learning El-Melegy, Mamdouh, Ali, Badawy, El-Ghar, Alghamdi, El-Baz
Bioengineering, 2024, Volume 11, Issue 7, Pages 635.

A machine learning-based approach for individualized prediction of short-term outcomes after anterior cervical corpectomy Karabacak, Schupper, Carr, Margetis
Asian Spine Journal, 2024, Volume 18, Issue 4, Pages 541.

Comparing the Performance of a Deep Learning Model (TabPFN) for Predicting River Algal Blooms with Varying Data Composition Yang, Park
Journal of Wetlands Research, 2024, Volume 26, Issue 3, Pages 197--203.

Adapting TabPFN for Zero-Inflated Metagenomic Data Perciballi, Granese, Fall, Zehraoui, Prifti, Zucker
NeurIPS 2024 Third Table Representation Learning Workshop, No Year.

Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer Dyikanov, Zaitsev, Vasileva, Wang, Sokolov, Bolshakov, Frank, Turova, Golubeva, Gantseva, others
Cancer Cell, 2024, Volume 42, Issue 5, Pages 759--779.

Predicting dementia in Parkinson's disease on a small tabular dataset using hybrid LightGBM--TabPFN and SHAP Tran, Byeon
Digital Health, 2024, Volume 10, Pages 20552076241272585.

Enhancing actuarial non-life pricing models via transformers Brauer
European Actuarial Journal, 2024, Pages 1--22.

Machine learning-based diagnostic prediction of minimal change disease: model development study Noda, Ichikawa, Shibagaki
Scientific Reports, 2024, Volume 14, Issue 1, Pages 23460.

Using AutoML and generative AI to predict the type of wildfire propagation in Canadian conifer forests Khanmohammadi, Cruz, Perrakis, Alexander, Arashpour
Ecological Informatics, 2024, Volume 82, Pages 102711.

Machine learning applications on lunar meteorite minerals: From classification to mechanical properties prediction Pe{~n}a-Asensio, Trigo-Rodr{'\i}guez, Sort, Ib{'a}{~n}ez-Insa, Rimola
International Journal of Mining Science and Technology, 2024.

Data-Driven Prognostication in Distal Medium Vessel Occlusions Using Explainable Machine Learning Karabacak, Ozkara, Faizy, Hardigan, Heit, Lakhani, Margetis, Mocco, Nael, Wintermark, others
American Journal of Neuroradiology, 2024.