:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Senetaire, Hugo, Jeha, Paul, Mattei, Pierre-Alexandre, Frellsen, Jes
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2503.07021
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explainability as statistical inference
by: Senetaire, Hugo Henri Joseph, et al.
Published: (2022)

Variance reduction of diffusion model's gradients with Taylor approximation-based control variate
by: Jeha, Paul, et al.
Published: (2024)

Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
by: Jeha, Paul, et al.
Published: (2026)

Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo
by: Lee, Cheuk Kit, et al.
Published: (2025)

Noise-Response Calibration: A Causal Intervention Protocol for LLM-Judges
by: Khomiakov, Maxim, et al.
Published: (2026)

Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters
by: Arts, Marloes, et al.
Published: (2023)

Order-Agnostic Autoregressive Modelling with Missing Data
by: Peis, Ignacio, et al.
Published: (2026)

MolMiner: Towards Controllable, 3D-Aware, Fragment-Based Molecular Design
by: Ortega-Ochoa, Raul, et al.
Published: (2024)

Hyper-Transforming Latent Diffusion Models
by: Peis, Ignacio, et al.
Published: (2025)

Fast Sampling for Flows and Diffusions with Lazy and Point Mass Stochastic Interpolants
by: Damsholt, Gabriel, et al.
Published: (2026)

Latent Diffusion for Missing Data
by: Estad, Alberte Heering, et al.
Published: (2026)

An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms
by: Grünefeld, Nils, et al.
Published: (2026)

Navigating Uncertainty in Medical Image Segmentation
by: Zepf, Kilian, et al.
Published: (2024)

Supervised Guidance Training for Infinite-Dimensional Diffusion Models
by: Baker, Elizabeth L., et al.
Published: (2026)

Exploring bidirectional bounds for minimax-training of Energy-based models
by: Geng, Cong, et al.
Published: (2025)

Bayesian Circular Regression with von Mises Quasi-Processes
by: Cohen, Yarden, et al.
Published: (2024)

Generative Diffusion Models for Sequential Recommendations
by: Zolghadr, Sharare, et al.
Published: (2024)

Kinetic Langevin Diffusion for Crystalline Materials Generation
by: Cornet, François, et al.
Published: (2025)

A Continuous Relaxation for Discrete Bayesian Optimization
by: Michael, Richard, et al.
Published: (2024)

Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means
by: Razafindralambo, Raphaël, et al.
Published: (2026)

Tracing Uncertainty in Language Model "Reasoning"
by: Grünefeld, Nils, et al.
Published: (2026)

Scalable physical source-to-field inference with hypernetworks
by: James, Berian, et al.
Published: (2024)

Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
by: Zhu, Yaxuan, et al.
Published: (2023)

Are Ensembles Getting Better all the Time?
by: Mattei, Pierre-Alexandre, et al.
Published: (2023)

The Well-Tempered Classifier: Some Elementary Properties of Temperature Scaling
by: Mattei, Pierre-Alexandre, et al.
Published: (2026)

A Tutorial on Discriminative Clustering and Mutual Information
by: Ohl, Louis, et al.
Published: (2025)

MXNorm: Reusing MXFP block scales for efficient tensor normalisation
by: McLean, Callum, et al.
Published: (2026)

Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
by: Zepf, Kilian, et al.
Published: (2023)

Parsimonious Gaussian mixture models with piecewise-constant eigenvalue profiles
by: Szwagier, Tom, et al.
Published: (2025)

Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
by: Frellsen, Jes, et al.
Published: (2025)

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations
by: Kruse, Johannes, et al.
Published: (2024)

EB-NeRD: A Large-Scale Dataset for News Recommendation
by: Kruse, Johannes, et al.
Published: (2024)

Kernel KMeans clustering splits for end-to-end unsupervised decision trees
by: Ohl, Louis, et al.
Published: (2024)

Likelihood-guided Regularization in Attention Based Models
by: Salem, Mohamed, et al.
Published: (2025)

When Are Two Scores Better Than One? Investigating Ensembles of Diffusion Models
by: Razafindralambo, Raphaël, et al.
Published: (2026)

Maximum Likelihood Reinforcement Learning
by: Tajwar, Fahim, et al.
Published: (2026)

Credal Prediction based on Relative Likelihood
by: Löhr, Timo, et al.
Published: (2025)

Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models
by: Erives, Ezra, et al.
Published: (2024)

Fault injection analysis of Real NVP normalising flow model for satellite anomaly detection
by: Greco, Gabriele, et al.
Published: (2025)

CREPE: Controlling Diffusion with Replica Exchange
by: He, Jiajun, et al.
Published: (2025)