Saved in:
| Main Authors: | Zhang, Kevin, Wang, Yixin |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.04462 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Exponential Family Attention
by: Wibisono, Kevin Christian, et al.
Published: (2025)
by: Wibisono, Kevin Christian, et al.
Published: (2025)
Deep Generative Models: Complexity, Dimensionality, and Approximation
by: Wang, Kevin, et al.
Published: (2025)
by: Wang, Kevin, et al.
Published: (2025)
From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When
by: Wibisono, Kevin Christian, et al.
Published: (2024)
by: Wibisono, Kevin Christian, et al.
Published: (2024)
Stabilizing distribution-free probabilistic forecasts
by: Van Belle, Jente, et al.
Published: (2026)
by: Van Belle, Jente, et al.
Published: (2026)
Contextual Latent World Models for Offline Meta Reinforcement Learning
by: Nakheai, Mohammadreza, et al.
Published: (2026)
by: Nakheai, Mohammadreza, et al.
Published: (2026)
Quantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast Objects
by: Zhang, Yixin, et al.
Published: (2024)
by: Zhang, Yixin, et al.
Published: (2024)
Causal Inference for Human-Language Model Collaboration
by: Zhang, Bohan, et al.
Published: (2024)
by: Zhang, Bohan, et al.
Published: (2024)
Entropy regularization in probabilistic clustering
by: Franzolini, Beatrice, et al.
Published: (2023)
by: Franzolini, Beatrice, et al.
Published: (2023)
Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
by: Wang, Zhi, et al.
Published: (2024)
by: Wang, Zhi, et al.
Published: (2024)
Improved probabilistic regression using diffusion models
by: Kneissl, Carlo, et al.
Published: (2025)
by: Kneissl, Carlo, et al.
Published: (2025)
Comparing the information content of probabilistic representation spaces
by: Murphy, Kieran A., et al.
Published: (2024)
by: Murphy, Kieran A., et al.
Published: (2024)
Extending F1 metric, probabilistic approach
by: Sitarz, Mikolaj
Published: (2022)
by: Sitarz, Mikolaj
Published: (2022)
I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
by: Vashistha, Ritwik, et al.
Published: (2025)
by: Vashistha, Ritwik, et al.
Published: (2025)
Optimal probabilistic feature shifts for reclassification in tree ensembles
by: Blanco, Víctor, et al.
Published: (2024)
by: Blanco, Víctor, et al.
Published: (2024)
QxEAI: Quantum-like evolutionary algorithm for automated probabilistic forecasting
by: Xin, Kevin, et al.
Published: (2024)
by: Xin, Kevin, et al.
Published: (2024)
How to select slices for annotation to train best-performing deep learning segmentation models for cross-sectional medical images?
by: Zhang, Yixin, et al.
Published: (2024)
by: Zhang, Yixin, et al.
Published: (2024)
On the physics of nested Markov models: a generalized probabilistic theory perspective
by: Zhang, Xingjian, et al.
Published: (2024)
by: Zhang, Xingjian, et al.
Published: (2024)
Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
by: Ousherovitch, Adam, et al.
Published: (2026)
by: Ousherovitch, Adam, et al.
Published: (2026)
Likelihood hacking in probabilistic program synthesis
by: Karwowski, Jacek, et al.
Published: (2026)
by: Karwowski, Jacek, et al.
Published: (2026)
Measuring memorization in language models via probabilistic extraction
by: Hayes, Jamie, et al.
Published: (2024)
by: Hayes, Jamie, et al.
Published: (2024)
Continual learning via probabilistic exchangeable sequence modelling
by: Xing, Hanwen, et al.
Published: (2025)
by: Xing, Hanwen, et al.
Published: (2025)
Discrete Causal Representation Learning
by: Zhang, Wenjin, et al.
Published: (2026)
by: Zhang, Wenjin, et al.
Published: (2026)
New probabilistic interest measures for association rules
by: Hahsler, Michael, et al.
Published: (2008)
by: Hahsler, Michael, et al.
Published: (2008)
Towards efficient quantum algorithms for diffusion probabilistic models
by: Wang, Yunfei, et al.
Published: (2025)
by: Wang, Yunfei, et al.
Published: (2025)
Variational Schrödinger Momentum Diffusion
by: Rojas, Kevin, et al.
Published: (2025)
by: Rojas, Kevin, et al.
Published: (2025)
Causal Representation Meets Stochastic Modeling under Generic Geometry
by: Ren, Jiaxu, et al.
Published: (2026)
by: Ren, Jiaxu, et al.
Published: (2026)
Deep classifier kriging for probabilistic spatial prediction of air quality index
by: Chen, Junyu, et al.
Published: (2025)
by: Chen, Junyu, et al.
Published: (2025)
NBMLSS: probabilistic forecasting of electricity prices via Neural Basis Models for Location Scale and Shape
by: Brusaferri, Alessandro, et al.
Published: (2024)
by: Brusaferri, Alessandro, et al.
Published: (2024)
Environment-Adaptive Covariate Selection: Learning When to Use Spurious Correlations for Out-of-Distribution Prediction
by: Zuo, Shuozhi, et al.
Published: (2026)
by: Zuo, Shuozhi, et al.
Published: (2026)
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
by: Xu, Zhiwei, et al.
Published: (2025)
by: Xu, Zhiwei, et al.
Published: (2025)
MetaEformer: Unveiling and Leveraging Meta-patterns for Complex and Dynamic Systems Load Forecasting
by: Huang, Shaoyuan, et al.
Published: (2025)
by: Huang, Shaoyuan, et al.
Published: (2025)
nabqr: Python package for improving probabilistic forecasts
by: Jørgensena, Bastian Schmidt, et al.
Published: (2025)
by: Jørgensena, Bastian Schmidt, et al.
Published: (2025)
Round-trip Reinforcement Learning: Self-Consistent Training for Better Chemical LLMs
by: Kong, Lecheng, et al.
Published: (2025)
by: Kong, Lecheng, et al.
Published: (2025)
Complex Logical Query Answering by Calibrating Knowledge Graph Completion Models
by: Xiao, Changyi, et al.
Published: (2024)
by: Xiao, Changyi, et al.
Published: (2024)
LLMs are not (consistently) Bayesian: Quantifying internal (in)consistencies of LLMs' probabilistic beliefs
by: Chen, Chacha, et al.
Published: (2026)
by: Chen, Chacha, et al.
Published: (2026)
A probabilistic framework for dynamic quantization
by: Santini, Gabriele, et al.
Published: (2025)
by: Santini, Gabriele, et al.
Published: (2025)
Enforcing tail calibration when training probabilistic forecast models
by: Wessel, Jakob Benjamin, et al.
Published: (2025)
by: Wessel, Jakob Benjamin, et al.
Published: (2025)
Machine learning-based probabilistic forecasting of solar irradiance in Chile
by: Baran, Sándor, et al.
Published: (2024)
by: Baran, Sándor, et al.
Published: (2024)
An efficient probabilistic hardware architecture for diffusion-like models
by: Jelinčič, Andraž, et al.
Published: (2025)
by: Jelinčič, Andraž, et al.
Published: (2025)
Compositional meta-learning through probabilistic task inference
by: Bakermans, Jacob J. W., et al.
Published: (2025)
by: Bakermans, Jacob J. W., et al.
Published: (2025)
Similar Items
-
Exponential Family Attention
by: Wibisono, Kevin Christian, et al.
Published: (2025) -
Deep Generative Models: Complexity, Dimensionality, and Approximation
by: Wang, Kevin, et al.
Published: (2025) -
From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When
by: Wibisono, Kevin Christian, et al.
Published: (2024) -
Stabilizing distribution-free probabilistic forecasts
by: Van Belle, Jente, et al.
Published: (2026) -
Contextual Latent World Models for Offline Meta Reinforcement Learning
by: Nakheai, Mohammadreza, et al.
Published: (2026)