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tabular-classification

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Showing 1–48 of 48 papers

TitleStatusHype
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a SecondCode5
JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMsCode2
TabLLM: Few-shot Classification of Tabular Data with Large Language ModelsCode2
TabMixer: advancing tabular data analysis with an enhanced MLP-mixer approachCode1
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual ExplanationsCode1
PMLBmini: A Tabular Classification Benchmark Suite for Data-Scarce ApplicationsCode1
Pairwise Difference Learning for ClassificationCode1
ALPBench: A Benchmark for Active Learning Pipelines on Tabular DataCode1
TuneTables: Context Optimization for Scalable Prior-Data Fitted NetworksCode1
MotherNet: Fast Training and Inference via Hyper-Network TransformersCode1
Robust-GBDT: GBDT with Nonconvex Loss for Tabular Classification in the Presence of Label Noise and Class ImbalanceCode1
GANDALF: Gated Adaptive Network for Deep Automated Learning of FeaturesCode1
The GatedTabTransformer. An enhanced deep learning architecture for tabular modelingCode1
Revisiting Deep Learning Models for Tabular DataCode1
TabTransformer: Tabular Data Modeling Using Contextual EmbeddingsCode1
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?Code1
Generative Imputation and Stochastic PredictionCode1
Learning Interpretable Differentiable Logic Networks for Tabular Regression—0
Test-Time Training Provably Improves Transformers as In-context Learners—0
TabNSA: Native Sparse Attention for Efficient Tabular Data Learning—0
Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak LearnersCode0
What exactly has TabPFN learned to do?Code0
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems—0
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular ClassificationCode0
How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narrativesCode0
Bayesian Concept Bottleneck Models with LLM PriorsCode0
STAND: Data-Efficient and Self-Aware Precondition Induction for Interactive Task Learning—0
Improving GBDT Performance on Imbalanced Datasets: An Empirical Study of Class-Balanced Loss FunctionsCode0
Transformers with Stochastic Competition for Tabular Data ModellingCode0
Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMs—0
MSBoost: Using Model Selection with Multiple Base Estimators for Gradient BoostingCode0
Tokenize features, enhancing tables: the FT-TABPFN model for tabular classification—0
Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications—0
Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks—0
The Disagreement Problem in Faithfulness Metrics—0
Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications—0
Improve Deep Forest with Learnable Layerwise Augmentation Policy ScheduleCode0
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck—0
A Suite of Fairness Datasets for Tabular Classification—0
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization—0
Is margin all you need? An extensive empirical study of active learning on tabular data—0
PTab: Using the Pre-trained Language Model for Modeling Tabular Data—0
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble ModelsCode0
Fieldwise Factorized Networks for Tabular Data Classification—0
CARE: Coherent Actionable Recourse based on Sound Counterfactual ExplanationsCode0
SCARF: Self-Supervised Contrastive Learning using Random Feature CorruptionCode0
Metalearning Using Structure-rich Pipeline Representations for Better AutoML—0
Ensemble Squared: A Meta AutoML System—0
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