Cover Image

Variance reduction of diffusion model's gradients with Taylor approximation-based control variate

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jeha, Paul, Grathwohl, Will, Andersen, Michael Riis, Ek, Carl Henrik, Frellsen, Jes
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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)

Learning Energy-Based Models by Self-normalising the Likelihood
by: Senetaire, Hugo, et al.
Published: (2025)

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

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

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)

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

eagle: early approximated gradient based learning rate estimator
by: Fujimoto, Takumi, et al.
Published: (2025)

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

Impartial Games: A Challenge for Reinforcement Learning
by: Zhou, Bei, et al.
Published: (2022)

GeoFormer: A Multi-Polygon Segmentation Transformer
by: Khomiakov, Maxim, et al.
Published: (2024)

Bayesian Nonparametric Dynamical Clustering of Time Series
by: Pérez-Herrero, Adrián, et al.
Published: (2025)

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

Conditional score-based diffusion models for solving inverse problems in mechanics
by: Dasgupta, Agnimitra, et al.
Published: (2024)

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

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

Low Variance Off-policy Evaluation with State-based Importance Sampling
by: Bossens, David M., et al.
Published: (2022)

TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models
by: Tang, Yuchi, et al.
Published: (2025)

Quantifying Variance in Evaluation Benchmarks
by: Madaan, Lovish, et al.
Published: (2024)

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

IDEQ: an improved diffusion model for the TSP
by: Basson, Mickael, et al.
Published: (2024)

On conditional diffusion models for PDE simulations
by: Shysheya, Aliaksandra, et al.
Published: (2024)

A foundation model with multi-variate parallel attention to generate neuronal activity
by: Carzaniga, Francesco, et al.
Published: (2025)

On Vanishing Variance in Transformer Length Generalization
by: Li, Ruining, et al.
Published: (2025)

On Variance Reduction in Learning Mean Flows
by: Lu, Juanwu, et al.
Published: (2026)

Localising Dropout Variance in Twin Networks
by: Doyle, Cooper
Published: (2025)

Generative method for aerodynamic optimization based on classifier-free guided denoising diffusion probabilistic model
by: Deng, Shisong, et al.
Published: (2025)

Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder
by: Akhtar, Sheikh Waqas
Published: (2024)

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

An overview of diffusion models for generative artificial intelligence
by: Gallon, Davide, et al.
Published: (2024)

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

Analyzing Generalization in Pre-Trained Symbolic Regression
by: Voigt, Henrik, et al.
Published: (2025)

Uncertainty Estimation using Variance-Gated Distributions
by: Gillis, H. Martin, et al.
Published: (2025)

An efficient probabilistic hardware architecture for diffusion-like models
by: Jelinčič, Andraž, et al.
Published: (2025)

Variance-Dependent Regret Lower Bounds for Contextual Bandits
by: He, Jiafan, et al.
Published: (2025)

A Variance Minimization Approach to Temporal-Difference Learning
by: Chen, Xingguo, et al.
Published: (2024)

Adaptive Variance-Penalized Continual Learning with Fisher Regularization
by: Sarkar, Krisanu
Published: (2025)