Saved in:
| Main Authors: | Schodt, David J., Brown, Ryan, Merritt, Michael, Park, Samuel, Menolascino, Delsin, Peot, Mark A. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.14532 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Few-sample Variational Inference of Bayesian Neural Networks with Arbitrary Nonlinearities
by: Schodt, David J.
Published: (2024)
by: Schodt, David J.
Published: (2024)
Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization
by: Sinaga, Marshal Arijona, et al.
Published: (2024)
by: Sinaga, Marshal Arijona, et al.
Published: (2024)
Heteroscedastic Neural Networks for Path Loss Prediction with Link-Specific Uncertainty
by: Ethier, Jonathan
Published: (2025)
by: Ethier, Jonathan
Published: (2025)
Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference
by: Gebre, Tewodros Syum, et al.
Published: (2026)
by: Gebre, Tewodros Syum, et al.
Published: (2026)
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
by: Gelberg, Yoav, et al.
Published: (2024)
by: Gelberg, Yoav, et al.
Published: (2024)
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
by: Li, Junbo, et al.
Published: (2024)
by: Li, Junbo, et al.
Published: (2024)
Heteroscedastic Double Bayesian Elastic Net
by: Kimura, Masanari
Published: (2025)
by: Kimura, Masanari
Published: (2025)
Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference
by: Bera, Pavia, et al.
Published: (2025)
by: Bera, Pavia, et al.
Published: (2025)
H-AddiVortes: Heteroscedastic (Bayesian) Additive Voronoi Tessellations
by: Stone, Adam J., et al.
Published: (2025)
by: Stone, Adam J., et al.
Published: (2025)
Heteroscedastic Temporal Variational Autoencoder For Irregular Time Series
by: Shukla, Satya Narayan, et al.
Published: (2021)
by: Shukla, Satya Narayan, et al.
Published: (2021)
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
by: Descours, Arnaud, et al.
Published: (2024)
by: Descours, Arnaud, et al.
Published: (2024)
Large-scale Score-based Variational Posterior Inference for Bayesian Deep Neural Networks
by: Kim, Minyoung
Published: (2026)
by: Kim, Minyoung
Published: (2026)
Variational Graph Neural Networks for Uncertainty Quantification in Inverse Problems
by: Gonzalez, David, et al.
Published: (2026)
by: Gonzalez, David, et al.
Published: (2026)
Real-Time Structural Health Monitoring with Bayesian Neural Networks: Distinguishing Aleatoric and Epistemic Uncertainty for Digital Twin Frameworks
by: Cho, Hanbin, et al.
Published: (2025)
by: Cho, Hanbin, et al.
Published: (2025)
Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
by: Sheinkman, Alisa, et al.
Published: (2025)
by: Sheinkman, Alisa, et al.
Published: (2025)
Uncertainty Prediction Neural Network (UpNet): Embedding Artificial Neural Network in Bayesian Inversion Framework to Quantify the Uncertainty of Remote Sensing Retrieval
by: Fan, Dasheng, et al.
Published: (2024)
by: Fan, Dasheng, et al.
Published: (2024)
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
by: Manas, Kumar, et al.
Published: (2025)
by: Manas, Kumar, et al.
Published: (2025)
A Variational Approach to Bayesian Phylogenetic Inference
by: Zhang, Cheng, et al.
Published: (2022)
by: Zhang, Cheng, et al.
Published: (2022)
Microstructure-based Variational Neural Networks for Robust Uncertainty Quantification in Materials Digital Twins
by: Robertson, Andreas E., et al.
Published: (2025)
by: Robertson, Andreas E., et al.
Published: (2025)
The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
by: Koermer, Scott, et al.
Published: (2025)
by: Koermer, Scott, et al.
Published: (2025)
The Epistemic Uncertainty Hole: an issue of Bayesian Neural Networks
by: Fellaji, Mohammed, et al.
Published: (2024)
by: Fellaji, Mohammed, et al.
Published: (2024)
Variational Inference on the Final-Layer Output of Neural Networks
by: Wei, Yadi, et al.
Published: (2023)
by: Wei, Yadi, et al.
Published: (2023)
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
by: Young, Spencer, et al.
Published: (2024)
by: Young, Spencer, et al.
Published: (2024)
Inference in Partially Linear Models under Dependent Data with Deep Neural Networks
by: Brown, Chad
Published: (2024)
by: Brown, Chad
Published: (2024)
Cooperative Variance Estimation and Bayesian Neural Networks for Disentangling Aleatoric and Epistemic Uncertainties
by: Yi, Jiaxiang, et al.
Published: (2025)
by: Yi, Jiaxiang, et al.
Published: (2025)
ALPCAHUS: Subspace Clustering for Heteroscedastic Data
by: Cavazos, Javier Salazar, et al.
Published: (2025)
by: Cavazos, Javier Salazar, et al.
Published: (2025)
Singular Bayesian Neural Networks
by: Toure, Mame Diarra, et al.
Published: (2026)
by: Toure, Mame Diarra, et al.
Published: (2026)
Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks
by: Li, Yi, et al.
Published: (2025)
by: Li, Yi, et al.
Published: (2025)
The Bayesian Confidence (BACON) Estimator for Deep Neural Networks
by: Kee, Patrick D., et al.
Published: (2024)
by: Kee, Patrick D., et al.
Published: (2024)
Variational Inference for Bayesian MIDAS Regression
by: Simeone, Luigi
Published: (2026)
by: Simeone, Luigi
Published: (2026)
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)
Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks
by: Pilar, Philipp, et al.
Published: (2025)
by: Pilar, Philipp, et al.
Published: (2025)
BALI: Learning Neural Networks via Bayesian Layerwise Inference
by: Kurle, Richard, et al.
Published: (2024)
by: Kurle, Richard, et al.
Published: (2024)
Low-Budget Simulation-Based Inference with Bayesian Neural Networks
by: Delaunoy, Arnaud, et al.
Published: (2024)
by: Delaunoy, Arnaud, et al.
Published: (2024)
Variational Bayesian Bow tie Neural Networks with Shrinkage
by: Sheinkman, Alisa, et al.
Published: (2024)
by: Sheinkman, Alisa, et al.
Published: (2024)
Federated Variational Inference for Bayesian Mixture Models
by: Rao, Jackie, et al.
Published: (2025)
by: Rao, Jackie, et al.
Published: (2025)
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective
by: Yuan, Xueqiong, et al.
Published: (2025)
by: Yuan, Xueqiong, et al.
Published: (2025)
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
by: Shih, Frank, et al.
Published: (2025)
by: Shih, Frank, et al.
Published: (2025)
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions
by: Xie, Tianyu, et al.
Published: (2024)
by: Xie, Tianyu, et al.
Published: (2024)
Bayesian Optimization of a Lightweight and Accurate Neural Network for Aerodynamic Performance Prediction
by: Shihua, James M., et al.
Published: (2025)
by: Shihua, James M., et al.
Published: (2025)
Similar Items
-
Few-sample Variational Inference of Bayesian Neural Networks with Arbitrary Nonlinearities
by: Schodt, David J.
Published: (2024) -
Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization
by: Sinaga, Marshal Arijona, et al.
Published: (2024) -
Heteroscedastic Neural Networks for Path Loss Prediction with Link-Specific Uncertainty
by: Ethier, Jonathan
Published: (2025) -
Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference
by: Gebre, Tewodros Syum, et al.
Published: (2026) -
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
by: Gelberg, Yoav, et al.
Published: (2024)