Bayesian Inverse Problems with Conditional Sinkhorn Generative Adversarial Networks in Least Volume Latent Spaces
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Qiuyi, Tsilifis, Panagiotis, Fuge, Mark |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Least Volume Analysis
by: Chen, Qiuyi, et al.
Published: (2024)
by: Chen, Qiuyi, et al.
Published: (2024)
Inverse design with conditional cascaded diffusion models
by: Habibi, Milad, et al.
Published: (2024)
by: Habibi, Milad, et al.
Published: (2024)
Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
by: Chen, Youguang, et al.
Published: (2026)
by: Chen, Youguang, et al.
Published: (2026)
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
by: Altekrüger, Fabian, et al.
Published: (2023)
by: Altekrüger, Fabian, et al.
Published: (2023)
Preconditioned One-Step Generative Modeling for Bayesian Inverse Problems in Function Spaces
by: Cheng, Zilan, et al.
Published: (2026)
by: Cheng, Zilan, et al.
Published: (2026)
Adaptive Learning of the Latent Space of Wasserstein Generative Adversarial Networks
by: Qiu, Yixuan, et al.
Published: (2024)
by: Qiu, Yixuan, et al.
Published: (2024)
Bayesian Conditioned Diffusion Models for Inverse Problems
by: Güngör, Alper, et al.
Published: (2024)
by: Güngör, Alper, et al.
Published: (2024)
Prediction Markets as Bayesian Inverse Problems: Uncertainty Quantification, Identifiability, and Information Gain from Price-Volume Histories under Latent Types
by: Madrigal-Cianci, Juan Pablo, et al.
Published: (2026)
by: Madrigal-Cianci, Juan Pablo, et al.
Published: (2026)
Sinkhorn-Drifting Generative Models
by: He, Ping, et al.
Published: (2026)
by: He, Ping, et al.
Published: (2026)
Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesis
by: Nasution, Bahrul Ilmi, et al.
Published: (2026)
by: Nasution, Bahrul Ilmi, et al.
Published: (2026)
Proximal-Based Generative Modeling for Bayesian Inverse Problems
by: Zhang, Boyang, et al.
Published: (2026)
by: Zhang, Boyang, et al.
Published: (2026)
GLUE: Coordinating Pre-Trained Generative Models for System-Level Design
by: Aebersold, Tim, et al.
Published: (2025)
by: Aebersold, Tim, et al.
Published: (2025)
Latent Space Translation via Inverse Relative Projection
by: Maiorca, Valentino, et al.
Published: (2024)
by: Maiorca, Valentino, et al.
Published: (2024)
SD-CGAN: Conditional Sinkhorn Divergence GAN for DDoS Anomaly Detection in IoT Networks
by: Onyeka, Henry, et al.
Published: (2025)
by: Onyeka, Henry, et al.
Published: (2025)
Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
Spatiotemporal Besov Priors for Bayesian Inverse Problems
by: Lan, Shiwei, et al.
Published: (2023)
by: Lan, Shiwei, et al.
Published: (2023)
Latent Generative Models with Tunable Complexity for Compressed Sensing and other Inverse Problems
by: Gunn, Sean, et al.
Published: (2026)
by: Gunn, Sean, et al.
Published: (2026)
Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo
by: Achituve, Idan, et al.
Published: (2025)
by: Achituve, Idan, et al.
Published: (2025)
Time-Aware Latent Space Bayesian Optimization
by: Vu, Tuan A., et al.
Published: (2026)
by: Vu, Tuan A., et al.
Published: (2026)
Joint Composite Latent Space Bayesian Optimization
by: Maus, Natalie, et al.
Published: (2023)
by: Maus, Natalie, et al.
Published: (2023)
Latent Space Bayesian Optimization with Latent Data Augmentation for Enhanced Exploration
by: Boyar, Onur, et al.
Published: (2023)
by: Boyar, Onur, et al.
Published: (2023)
A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations
by: Gupta, Naveen, et al.
Published: (2024)
by: Gupta, Naveen, et al.
Published: (2024)
Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds
by: Zhang, Shuhai, et al.
Published: (2024)
by: Zhang, Shuhai, et al.
Published: (2024)
CTTVAE: Latent Space Structuring for Conditional Tabular Data Generation on Imbalanced Datasets
by: Devic, Milosh, et al.
Published: (2026)
by: Devic, Milosh, et al.
Published: (2026)
GenPANIS: A Latent-Variable Generative Framework for Forward and Inverse PDE Problems in Multiphase Media
by: Chatzopoulos, Matthaios, et al.
Published: (2026)
by: Chatzopoulos, Matthaios, et al.
Published: (2026)
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems
by: Orozco, Rafael, et al.
Published: (2024)
by: Orozco, Rafael, et al.
Published: (2024)
Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
by: Yang, Yiming, et al.
Published: (2026)
by: Yang, Yiming, et al.
Published: (2026)
Compressive sensing adaptation for polynomial chaos expansions
by: Tsilifis, Panagiotis, et al.
Published: (2018)
by: Tsilifis, Panagiotis, et al.
Published: (2018)
Neural Sinkhorn Gradient Flow
by: Zhu, Huminhao, et al.
Published: (2024)
by: Zhu, Huminhao, et al.
Published: (2024)
Bayesian Physics-Informed Neural Networks for Inverse Problems (BPINN-IP): Application in Infrared Image Processing
by: Mohammad-Djafari, Ali, et al.
Published: (2025)
by: Mohammad-Djafari, Ali, et al.
Published: (2025)
Beyond Inference-Time Search: Reinforcement Learning Synthesizes Reusable Solvers
by: Massoudi, Soheyl, et al.
Published: (2026)
by: Massoudi, Soheyl, et al.
Published: (2026)
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network
by: Sun, Tan, et al.
Published: (2024)
by: Sun, Tan, et al.
Published: (2024)
Latent Neural Operator for Solving Forward and Inverse PDE Problems
by: Wang, Tian, et al.
Published: (2024)
by: Wang, Tian, et al.
Published: (2024)
Inverse Optimization Latent Variable Models for Learning Costs Applied to Route Problems
by: Lahoud, Alan A., et al.
Published: (2025)
by: Lahoud, Alan A., et al.
Published: (2025)
Repulsive Latent Score Distillation for Solving Inverse Problems
by: Zilberstein, Nicolas, et al.
Published: (2024)
by: Zilberstein, Nicolas, et al.
Published: (2024)
CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems
by: Jacobsen, Christian, et al.
Published: (2023)
by: Jacobsen, Christian, et al.
Published: (2023)
Federated Sinkhorn
by: Kulcsar, Jeremy, et al.
Published: (2025)
by: Kulcsar, Jeremy, et al.
Published: (2025)
Geometry-Free Conditional Diffusion Modeling for Solving the Inverse Electrocardiography Problem
by: Jara, Ramiro Valdes, et al.
Published: (2026)
by: Jara, Ramiro Valdes, et al.
Published: (2026)
SILO: Solving Inverse Problems with Latent Operators
by: Raphaeli, Ron, et al.
Published: (2025)
by: Raphaeli, Ron, et al.
Published: (2025)
Confident Sinkhorn Allocation for Pseudo-Labeling
by: Nguyen, Vu, et al.
Published: (2022)
by: Nguyen, Vu, et al.
Published: (2022)
Similar Items
-
Least Volume Analysis
by: Chen, Qiuyi, et al.
Published: (2024) -
Inverse design with conditional cascaded diffusion models
by: Habibi, Milad, et al.
Published: (2024) -
Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
by: Chen, Youguang, et al.
Published: (2026) -
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
by: Altekrüger, Fabian, et al.
Published: (2023) -
Preconditioned One-Step Generative Modeling for Bayesian Inverse Problems in Function Spaces
by: Cheng, Zilan, et al.
Published: (2026)