:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Papamarkou, Theodore, Skoularidou, Maria, Palla, Konstantina, Aitchison, Laurence, Arbel, Julyan, Dunson, David, Filippone, Maurizio, Fortuin, Vincent, Hennig, Philipp, Hernández-Lobato, José Miguel, Hubin, Aliaksandr, Immer, Alexander, Karaletsos, Theofanis, Khan, Mohammad Emtiyaz, Kristiadi, Agustinus, Li, Yingzhen, Mandt, Stephan, Nemeth, Christopher, Osborne, Michael A., Rudner, Tim G. J., Rügamer, David, Teh, Yee Whye, Welling, Max, Wilson, Andrew Gordon, Zhang, Ruqi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2402.00809
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Introduction to the Analysis of Probabilistic Decision-Making Algorithms
by: Kristiadi, Agustinus
Published: (2025)

Can Transformers Learn Full Bayesian Inference in Context?
by: Reuter, Arik, et al.
Published: (2025)

Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
by: Hubin, Aliaksandr
Published: (2025)

Variational Control for Guidance in Diffusion Models
by: Pandey, Kushagra, et al.
Published: (2025)

How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?
by: Kristiadi, Agustinus, et al.
Published: (2024)

Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
by: Bereket, Michael, et al.
Published: (2023)

How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset
by: Mohan, Sunil, et al.
Published: (2025)

On the Disconnect Between Theory and Practice of Neural Networks: Limits of the NTK Perspective
by: Wenger, Jonathan, et al.
Published: (2023)

Limits of PRM-Guided Tree Search for Mathematical Reasoning with LLMs
by: Cinquin, Tristan, et al.
Published: (2025)

Natural Variational Annealing for Multimodal Optimization
by: LeMinh, Tâm, et al.
Published: (2025)

Parallel Token Prediction for Language Models
by: Draxler, Felix, et al.
Published: (2025)

Calibrated Test-Time Guidance for Bayesian Inference
by: Geyfman, Daniel, et al.
Published: (2026)

Gaussian Pre-Activations in Neural Networks: Myth or Reality?
by: Wolinski, Pierre, et al.
Published: (2022)

Just rotate it! Uncertainty estimation in closed-source models via multiple queries
by: Pitas, Konstantinos, et al.
Published: (2024)

Position: agentic AI orchestration should be Bayes-consistent
by: Papamarkou, Theodore, et al.
Published: (2026)

FlashMD: long-stride, universal prediction of molecular dynamics
by: Bigi, Filippo, et al.
Published: (2025)

Toward Identifiable Sparse Autoencoders
by: Nelson, Walter, et al.
Published: (2026)

Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
by: Bao, Yujia, et al.
Published: (2023)

Compositional Deep Probabilistic Models of DNA Encoded Libraries
by: Chen, Benson, et al.
Published: (2023)

Optimal sub-Gaussian variance proxy for truncated Gaussian and exponential random variables
by: Barreto, Mathias, et al.
Published: (2024)

Optimal sub-Gaussian variance proxy for 3-mass distributions
by: Atouani, Soufiane, et al.
Published: (2025)

Shrinkage for Extreme Partial Least-Squares
by: Arbel, Julyan, et al.
Published: (2024)

Low-Rank Filtering and Smoothing for Sequential Deep Learning
by: Sliwa, Joanna, et al.
Published: (2024)

A Critical Look At Tokenwise Reward-Guided Text Generation
by: Rashid, Ahmad, et al.
Published: (2024)

Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks
by: Rashid, Ahmad, et al.
Published: (2023)

MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
by: Demirel, Berker, et al.
Published: (2025)

Statistical and structural identifiability in representation learning
by: Nelson, Walter, et al.
Published: (2026)

Improving Neural Additive Models with Bayesian Principles
by: Bouchiat, Kouroche, et al.
Published: (2023)

Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood
by: Dhahri, Rayen, et al.
Published: (2024)

Incorporating Unlabelled Data into Bayesian Neural Networks
by: Sharma, Mrinank, et al.
Published: (2023)

Simulation-based inference of yeast centromeres
by: Touron, Eloïse, et al.
Published: (2025)

$\textit{BlockFormer}$ : Transformer-based inference from interaction maps
by: Touron, Eloïse, et al.
Published: (2026)

On the Effect of Regularization on Nonparametric Mean-Variance Regression
by: Wong-Toi, Eliot, et al.
Published: (2025)

Understanding Pathologies of Deep Heteroskedastic Regression
by: Wong-Toi, Eliot, et al.
Published: (2023)

Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
by: Zhou, Julien, et al.
Published: (2024)

Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
by: Rosa, Rafael Mouallem, et al.
Published: (2026)

Position: Curvature Matrices Should Be Democratized via Linear Operators
by: Dangel, Felix, et al.
Published: (2025)

Towards Cost-Effective Reward Guided Text Generation
by: Rashid, Ahmad, et al.
Published: (2025)

Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models
by: Palla, Giovanni, et al.
Published: (2025)

FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging
by: Frommlet, Florian, et al.
Published: (2025)