Saved in:
| Main Authors: | Vetter, Julius, Gloeckler, Manuel, Gedon, Daniel, Macke, Jakob H. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.17660 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
by: Gloeckler, Manuel, et al.
Published: (2026)
by: Gloeckler, Manuel, et al.
Published: (2026)
Compositional simulation-based inference for time series
by: Gloeckler, Manuel, et al.
Published: (2024)
by: Gloeckler, Manuel, et al.
Published: (2024)
A Probabilistic Framework for LLM-Based Model Discovery
by: Wahl, Stefan, et al.
Published: (2026)
by: Wahl, Stefan, et al.
Published: (2026)
All-in-one simulation-based inference
by: Gloeckler, Manuel, et al.
Published: (2024)
by: Gloeckler, Manuel, et al.
Published: (2024)
Inferring stochastic low-rank recurrent neural networks from neural data
by: Pals, Matthijs, et al.
Published: (2024)
by: Pals, Matthijs, et al.
Published: (2024)
Mixed neural posterior estimation for simulators with discrete and continuous parameters
by: Boelts, Jan, et al.
Published: (2026)
by: Boelts, Jan, et al.
Published: (2026)
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
by: Vetter, Julius, et al.
Published: (2024)
by: Vetter, Julius, et al.
Published: (2024)
Simulation-Based Inference: A Practical Guide
by: Deistler, Michael, et al.
Published: (2025)
by: Deistler, Michael, et al.
Published: (2025)
Latent Diffusion for Neural Spiking Data
by: Kapoor, Jaivardhan, et al.
Published: (2024)
by: Kapoor, Jaivardhan, et al.
Published: (2024)
Revisiting CLIP: Efficient Alignment of 3D MRI and Tabular Data using Domain-Specific Foundation Models
by: Petersen, Jakob Krogh, et al.
Published: (2025)
by: Petersen, Jakob Krogh, et al.
Published: (2025)
A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science
by: Bischoff, Sebastian, et al.
Published: (2024)
by: Bischoff, Sebastian, et al.
Published: (2024)
Invertible Kernel PCA with Random Fourier Features
by: Gedon, Daniel, et al.
Published: (2023)
by: Gedon, Daniel, et al.
Published: (2023)
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
by: Shin, Changho, et al.
Published: (2024)
by: Shin, Changho, et al.
Published: (2024)
TabularFM: An Open Framework For Tabular Foundational Models
by: Tran, Quan M., et al.
Published: (2024)
by: Tran, Quan M., et al.
Published: (2024)
On Finetuning Tabular Foundation Models
by: Rubachev, Ivan, et al.
Published: (2025)
by: Rubachev, Ivan, et al.
Published: (2025)
Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models
by: Balef, Amir Rezaei, et al.
Published: (2026)
by: Balef, Amir Rezaei, et al.
Published: (2026)
Turning Tabular Foundation Models into Graph Foundation Models
by: Eremeev, Dmitry, et al.
Published: (2025)
by: Eremeev, Dmitry, et al.
Published: (2025)
Tabular Foundation Model for Generative Modelling
by: Jiang, Xiangjian, et al.
Published: (2026)
by: Jiang, Xiangjian, et al.
Published: (2026)
Valid Feature-Level Inference for Tabular Foundation Models via the Conditional Randomization Test
by: Salem, Mohamed
Published: (2026)
by: Salem, Mohamed
Published: (2026)
Robust Tabular Foundation Models
by: Peroni, Matthew, et al.
Published: (2025)
by: Peroni, Matthew, et al.
Published: (2025)
TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2025)
by: Tanna, Aditya, et al.
Published: (2025)
Can Graphs Improve Tabular Foundation Models?
by: Le, Franck, et al.
Published: (2025)
by: Le, Franck, et al.
Published: (2025)
Real-Time Explanations for Tabular Foundation Models
by: Sena, Luan Borges Teodoro Reis, et al.
Published: (2026)
by: Sena, Luan Borges Teodoro Reis, et al.
Published: (2026)
A Mechanistic Study of Tabular Foundation Models
by: Biloš, Marin, et al.
Published: (2026)
by: Biloš, Marin, et al.
Published: (2026)
Active In-Context Learning for Tabular Foundation Models
by: Treerath, Wilailuck, et al.
Published: (2026)
by: Treerath, Wilailuck, et al.
Published: (2026)
Exploring Fine-Tuning for Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2026)
by: Tanna, Aditya, et al.
Published: (2026)
End-to-End Compression for Tabular Foundation Models
by: Zabërgja, Guri, et al.
Published: (2026)
by: Zabërgja, Guri, et al.
Published: (2026)
On the Uncertainty Quantification Ability of Tabular Foundation Models
by: Johnson, Tyler R., et al.
Published: (2026)
by: Johnson, Tyler R., et al.
Published: (2026)
Tabular Foundation Models Can Learn Association Rules
by: Karabulut, Erkan, et al.
Published: (2026)
by: Karabulut, Erkan, et al.
Published: (2026)
Live Knowledge Tracing: Real-Time Adaptation using Tabular Foundation Models
by: Lbath, Mounir, et al.
Published: (2026)
by: Lbath, Mounir, et al.
Published: (2026)
Qrazor: Reliable and Effortless 4-bit LLM Quantization by Significant Data Razoring
by: Lee, Dongyoung, et al.
Published: (2025)
by: Lee, Dongyoung, et al.
Published: (2025)
MRExtrap: Longitudinal Aging of Brain MRIs using Linear Modeling in Latent Space
by: Kapoor, Jaivardhan, et al.
Published: (2025)
by: Kapoor, Jaivardhan, et al.
Published: (2025)
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
by: Fan, Chenghao, et al.
Published: (2024)
by: Fan, Chenghao, et al.
Published: (2024)
Towards Fair In-Context Learning with Tabular Foundation Models
by: Kenfack, Patrik, et al.
Published: (2025)
by: Kenfack, Patrik, et al.
Published: (2025)
Towards Benchmarking Foundation Models for Tabular Data With Text
by: Mráz, Martin, et al.
Published: (2025)
by: Mráz, Martin, et al.
Published: (2025)
Tabular Foundation Models Can Do Survival Analysis
by: Kim, Da In, et al.
Published: (2026)
by: Kim, Da In, et al.
Published: (2026)
VIP-COP: Context Optimization for Tabular Foundation Models
by: Chen, Yilong, et al.
Published: (2026)
by: Chen, Yilong, et al.
Published: (2026)
Tabular Foundation Models are Strong Graph Anomaly Detectors
by: Liu, Yunhui, et al.
Published: (2026)
by: Liu, Yunhui, et al.
Published: (2026)
TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields
by: Arazi, Alan, et al.
Published: (2025)
by: Arazi, Alan, et al.
Published: (2025)
Simultaneous identification of models and parameters of scientific simulators
by: Schröder, Cornelius, et al.
Published: (2023)
by: Schröder, Cornelius, et al.
Published: (2023)
Similar Items
-
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
by: Gloeckler, Manuel, et al.
Published: (2026) -
Compositional simulation-based inference for time series
by: Gloeckler, Manuel, et al.
Published: (2024) -
A Probabilistic Framework for LLM-Based Model Discovery
by: Wahl, Stefan, et al.
Published: (2026) -
All-in-one simulation-based inference
by: Gloeckler, Manuel, et al.
Published: (2024) -
Inferring stochastic low-rank recurrent neural networks from neural data
by: Pals, Matthijs, et al.
Published: (2024)