Cover Image

Probabilistic Bayesian optimal experimental design using conditional normalizing flows

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Orozco, Rafael, Herrmann, Felix J., Chen, Peng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine learning-enabled velocity model building with uncertainty quantification
by: Orozco, Rafael, et al.
Published: (2024)

Out-of-distribution detection using normalizing flows on the data manifold
by: Razavi, Seyedeh Fatemeh, et al.
Published: (2023)

Power-scaled Bayesian Inference with Score-based Generative Models
by: Erdinc, Huseyin Tuna, et al.
Published: (2025)

Probabilistic road classification in historical maps using synthetic data and deep learning
by: Mühlematter, Dominik J., et al.
Published: (2024)

Normalizing flow-based deep variational Bayesian network for seismic multi-hazards and impacts estimation from InSAR imagery
by: Li, Xuechun, et al.
Published: (2023)

PRBench: A Standardized Probabilistic Robustness Benchmark
by: Zhang, Yi, et al.
Published: (2025)

Video prediction using score-based conditional density estimation
by: Fiquet, Pierre-Étienne H., et al.
Published: (2024)

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
by: Lu, Cheng, et al.
Published: (2022)

Probabilistic Language-Image Pre-Training
by: Chun, Sanghyuk, et al.
Published: (2024)

Improved Probabilistic Image-Text Representations
by: Chun, Sanghyuk
Published: (2023)

Probabilistic Object Detection with Conformal Prediction
by: Ries, Christopher, et al.
Published: (2026)

Post-hoc Probabilistic Vision-Language Models
by: Baumann, Anton, et al.
Published: (2024)

Probabilistic Segmentation for Robust Field of View Estimation
by: Hallyburton, R. Spencer, et al.
Published: (2025)

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting
by: Jiang, Lingyu, et al.
Published: (2025)

BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averaging
by: Sherkatghanad, Zeinab, et al.
Published: (2024)

Probabilistic Contrastive Learning for Long-Tailed Visual Recognition
by: Du, Chaoqun, et al.
Published: (2024)

Stochastic Transition-Map Distillation for Fast Probabilistic Inference
by: Rapakoulias, George, et al.
Published: (2026)

Deep Clustering via Probabilistic Ratio-Cut Optimization
by: Ghriss, Ayoub, et al.
Published: (2025)

Probabilistic Deep Discriminant Analysis for Wind Blade Segmentation
by: Pérez-Gonzalo, Raül, et al.
Published: (2026)

Probabilistic Machine Learning for Noisy Labels in Earth Observation
by: Kondylatos, Spyros, et al.
Published: (2025)

Towards Desiderata-Driven Design of Visual Counterfactual Explainers
by: Bender, Sidney, et al.
Published: (2025)

Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks
by: Drees, Lukas, et al.
Published: (2023)

Understanding normalization in contrastive representation learning and out-of-distribution detection
by: Le-Gia, Tai, et al.
Published: (2023)

Probabilistic Precision and Recall Towards Reliable Evaluation of Generative Models
by: Park, Dogyun, et al.
Published: (2023)

Upstream Probabilistic Meta-Imputation for Multimodal Pediatric Pancreatitis Classification
by: Nelson, Max A., et al.
Published: (2025)

PVeRA: Probabilistic Vector-Based Random Matrix Adaptation
by: Fillioux, Leo, et al.
Published: (2025)

Generalized Evidential Deep Learning: From a Bayesian Perspective
by: Liu, Yuanye, et al.
Published: (2026)

Bayesian Diffusion Models for 3D Shape Reconstruction
by: Xu, Haiyang, et al.
Published: (2024)

On normalization-equivariance properties of supervised and unsupervised denoising methods: a survey
by: Herbreteau, Sébastien, et al.
Published: (2024)

Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation
by: Lee, Junha, et al.
Published: (2024)

PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
by: Xie, Haoyu, et al.
Published: (2024)

A Geometric Unification of Generative AI with Manifold-Probabilistic Projection Models
by: Bar, Leah, et al.
Published: (2025)

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models
by: Zeng, Qian, et al.
Published: (2025)

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
by: Zhang, Youjia, et al.
Published: (2025)

Provable Probabilistic Imaging using Score-Based Generative Priors
by: Sun, Yu, et al.
Published: (2023)

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference
by: Li, Chaojian, et al.
Published: (2021)

ProbMCL: Simple Probabilistic Contrastive Learning for Multi-label Visual Classification
by: Sajedi, Ahmad, et al.
Published: (2024)

PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification
by: Trędowicz, Magdalena, et al.
Published: (2024)

DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection
by: Bandara, Wele Gedara Chaminda, et al.
Published: (2022)

DiffECG: A Versatile Probabilistic Diffusion Model for ECG Signals Synthesis
by: Neifar, Nour, et al.
Published: (2023)