Saved in:
| Main Authors: | Sendera, Marcin, Sorkhei, Amin, Kuśmierczyk, Tomasz |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.08880 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations
by: Sendera, Marcin, et al.
Published: (2024)
by: Sendera, Marcin, et al.
Published: (2024)
TACTIC for Navigating the Unknown: Tabular Anomaly deteCTion via In-Context inference
by: Marszałek, Patryk, et al.
Published: (2026)
by: Marszałek, Patryk, et al.
Published: (2026)
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA
by: Marszałek, Patryk, et al.
Published: (2025)
by: Marszałek, Patryk, et al.
Published: (2025)
Bayesian Fine-tuning in Projected Subspaces
by: Dubovik, Viktar, et al.
Published: (2026)
by: Dubovik, Viktar, et al.
Published: (2026)
Efficient Uncertainty in LLMs through Evidential Knowledge Distillation
by: Nemani, Lakshmana Sri Harsha, et al.
Published: (2025)
by: Nemani, Lakshmana Sri Harsha, et al.
Published: (2025)
ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data
by: Marszałek, Patryk, et al.
Published: (2025)
by: Marszałek, Patryk, et al.
Published: (2025)
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training
by: Berner, Julius, et al.
Published: (2025)
by: Berner, Julius, et al.
Published: (2025)
SEMU: Singular Value Decomposition for Efficient Machine Unlearning
by: Sendera, Marcin, et al.
Published: (2025)
by: Sendera, Marcin, et al.
Published: (2025)
Solving Bayesian inverse problems with diffusion priors and off-policy RL
by: Scimeca, Luca, et al.
Published: (2025)
by: Scimeca, Luca, et al.
Published: (2025)
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models
by: Venkatraman, Siddarth, et al.
Published: (2025)
by: Venkatraman, Siddarth, et al.
Published: (2025)
Improved off-policy training of diffusion samplers
by: Sendera, Marcin, et al.
Published: (2024)
by: Sendera, Marcin, et al.
Published: (2024)
Transformer learns the cross-task prior and regularization for in-context learning
by: Lu, Fei, et al.
Published: (2025)
by: Lu, Fei, et al.
Published: (2025)
k-NN as a Simple and Effective Estimator of Transferability
by: Sorkhei, Moein, et al.
Published: (2025)
by: Sorkhei, Moein, et al.
Published: (2025)
On learning functions over biological sequence space: relating Gaussian process priors, regularization, and gauge fixing
by: Petti, Samantha, et al.
Published: (2025)
by: Petti, Samantha, et al.
Published: (2025)
Leveraging priors on distribution functions for multi-arm bandits
by: Vashishtha, Sumit, et al.
Published: (2025)
by: Vashishtha, Sumit, et al.
Published: (2025)
On the role of memorization in learned priors for geophysical inverse problems
by: Siahkoohi, Ali, et al.
Published: (2026)
by: Siahkoohi, Ali, et al.
Published: (2026)
Apprenticeship learning with prior beliefs using inverse optimization
by: Junca, Mauricio, et al.
Published: (2025)
by: Junca, Mauricio, et al.
Published: (2025)
Variational Autoregressive Networks with probability priors
by: Białas, Piotr, et al.
Published: (2026)
by: Białas, Piotr, et al.
Published: (2026)
Simple online learning with consistent oracle
by: Kozachinskiy, Alexander, et al.
Published: (2023)
by: Kozachinskiy, Alexander, et al.
Published: (2023)
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
by: Akhound-Sadegh, Tara, et al.
Published: (2024)
HiBBO: HiPPO-based Space Consistency for High-dimensional Bayesian Optimisation
by: Xuan, Junyu, et al.
Published: (2025)
by: Xuan, Junyu, et al.
Published: (2025)
Computable universal online learning
by: Kalociński, Dariusz, et al.
Published: (2025)
by: Kalociński, Dariusz, et al.
Published: (2025)
Incorporating priors in learning: a random matrix study under a teacher-student framework
by: Tiomoko, Malik, et al.
Published: (2025)
by: Tiomoko, Malik, et al.
Published: (2025)
Gaussian Process-based learning with new MCMC-based implementation of Wishart prior on correlation matrix
by: Warrior, Kane, et al.
Published: (2026)
by: Warrior, Kane, et al.
Published: (2026)
Evolutionary fine tuning of quantized convolution-based deep learning models
by: Pietroń, Marcin
Published: (2026)
by: Pietroń, Marcin
Published: (2026)
Influence functions and regularity tangents for efficient active learning
by: Eaton, Frederik
Published: (2024)
by: Eaton, Frederik
Published: (2024)
Deep learning model for ECG reconstruction reveals the information content of ECG leads
by: Gradowski, Tomasz, et al.
Published: (2025)
by: Gradowski, Tomasz, et al.
Published: (2025)
Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics
by: Chrabąszcz, Maciej, et al.
Published: (2026)
by: Chrabąszcz, Maciej, et al.
Published: (2026)
MLPrE -- A tool for preprocessing and exploratory data analysis prior to machine learning model construction
by: Maxwell, David S, et al.
Published: (2025)
by: Maxwell, David S, et al.
Published: (2025)
Mitigating covariate shift in non-colocated data with learned parameter priors
by: Khan, Behraj, et al.
Published: (2024)
by: Khan, Behraj, et al.
Published: (2024)
Representation learning in multiplex graphs: Where and how to fuse information?
by: Bielak, Piotr, et al.
Published: (2024)
by: Bielak, Piotr, et al.
Published: (2024)
A step towards the integration of machine learning and classic model-based survey methods
by: Żądło, Tomasz, et al.
Published: (2024)
by: Żądło, Tomasz, et al.
Published: (2024)
X-REFINE: XAI-based RElevance input-Filtering and archItecture fiNe-tuning for channel Estimation
by: Gizzini, Abdul Karim, et al.
Published: (2026)
by: Gizzini, Abdul Karim, et al.
Published: (2026)
Hi-GMAE: Hierarchical Graph Masked Autoencoders
by: Liu, Chuang, et al.
Published: (2024)
by: Liu, Chuang, et al.
Published: (2024)
Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks
by: Podhajski, Marcin, et al.
Published: (2024)
by: Podhajski, Marcin, et al.
Published: (2024)
Neural Koopman prior for data assimilation
by: Frion, Anthony, et al.
Published: (2023)
by: Frion, Anthony, et al.
Published: (2023)
Machine-learned models for magnetic materials
by: Leszczyński, Paweł, et al.
Published: (2023)
by: Leszczyński, Paweł, et al.
Published: (2023)
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
by: Sorkhei, Moein, et al.
Published: (2021)
by: Sorkhei, Moein, et al.
Published: (2021)
SeBA: Semi-supervised few-shot learning via Separated-at-Birth Alignment for tabular data
by: Jurek, Kacper, et al.
Published: (2026)
by: Jurek, Kacper, et al.
Published: (2026)
Generative emulation of chaotic dynamics with coherent prior
by: Nathaniel, Juan, et al.
Published: (2025)
by: Nathaniel, Juan, et al.
Published: (2025)
Similar Items
-
Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations
by: Sendera, Marcin, et al.
Published: (2024) -
TACTIC for Navigating the Unknown: Tabular Anomaly deteCTion via In-Context inference
by: Marszałek, Patryk, et al.
Published: (2026) -
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA
by: Marszałek, Patryk, et al.
Published: (2025) -
Bayesian Fine-tuning in Projected Subspaces
by: Dubovik, Viktar, et al.
Published: (2026) -
Efficient Uncertainty in LLMs through Evidential Knowledge Distillation
by: Nemani, Lakshmana Sri Harsha, et al.
Published: (2025)