Cover Image

Sequential Bayesian Neural Subnetwork Ensembles

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jantre, Sanket, Bhattacharya, Shrijita, Urban, Nathan M., Yoon, Byung-Jun, Maiti, Tapabrata, Balaprakash, Prasanna, Madireddy, Sandeep
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks
by: Jantre, Sanket, et al.
Published: (2023)

Large Language Models Inference Engines based on Spiking Neural Networks
by: Balaji, Adarsha, et al.
Published: (2025)

Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design
by: Abeer, A N M Nafiz, et al.
Published: (2024)

Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders
by: Abeer, A N M Nafiz, et al.
Published: (2024)

C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models
by: Rahmati, Amir Hossein, et al.
Published: (2025)

On Quantification of Borrowing of Information in Hierarchical Bayesian Models
by: Ghosh, Prasenjit, et al.
Published: (2025)

Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification
by: Jantre, Sanket, et al.
Published: (2025)

Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
by: Kungurtsev, Vyacheslav, et al.
Published: (2024)

Bayesian Design Principles for Frequentist Sequential Learning
by: Xu, Yunbei, et al.
Published: (2023)

Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction
by: Tang, Yin, et al.
Published: (2024)

Nonlinear Bayesian Update via Ensemble Kernel Regression with Clustering and Subsampling
by: Lee, Yoonsang
Published: (2025)

Ensembles of Neural Surrogates for Parametric Sensitivity in Ocean Modeling
by: Sun, Yixuan, et al.
Published: (2025)

Can Bayesian Neural Networks Make Confident Predictions?
by: Fisher, Katharine, et al.
Published: (2025)

Bayesian Semi-supervised Inference via a Debiased Modeling Approach
by: Sert, Gözde, et al.
Published: (2025)

Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
by: Sert, Gözde, et al.
Published: (2025)

Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis
by: Jantre, Sanket, et al.
Published: (2025)

Near-Optimal Non-Parametric Sequential Tests and Confidence Sequences with Possibly Dependent Observations
by: Bibaut, Aurelien, et al.
Published: (2022)

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)

Variational Bayesian Bow tie Neural Networks with Shrinkage
by: Sheinkman, Alisa, et al.
Published: (2024)

Small Ensemble-based Data Assimilation: A Machine Learning-Enhanced Data Assimilation Method with Limited Ensemble Size
by: Li, Zhilin, et al.
Published: (2025)

Asymptotically Optimal Sequential Testing with Markovian Data
by: Sethi, Alhad, et al.
Published: (2026)

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
by: Zhang, Haobo, et al.
Published: (2024)

Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
by: Descours, Arnaud, et al.
Published: (2024)

Tail-adaptive Bayesian shrinkage
by: Lee, Se Yoon, et al.
Published: (2020)

Sequential Kernelized Independence Testing
by: Podkopaev, Aleksandr, et al.
Published: (2022)

Deep Bayesian Inversion
by: Adler, Jonas, et al.
Published: (2018)

Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
by: Hasson, Hilaf, et al.
Published: (2023)

On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
by: Agrawal, Shubhada, et al.
Published: (2025)

Empirical Likelihood for Random Forests and Ensembles
by: Chiang, Harold D., et al.
Published: (2025)

Functional Sequential Treatment Allocation with Covariates
by: Kock, Anders Bredahl, et al.
Published: (2020)

Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs
by: Weill, Nathan, et al.
Published: (2026)

Boosting the Power of Kernel Two-Sample Tests
by: Chatterjee, Anirban, et al.
Published: (2023)

Robust Sequential Tracking via Bounded Information Geometry and Non-Parametric Field Actions
by: Rodriguez, Carlos C.
Published: (2026)

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
by: Elliott, Chris, et al.
Published: (2026)

On uncertainty-penalized Bayesian information criterion
by: Thanasutives, Pongpisit, et al.
Published: (2024)

Multi-Armed Sequential Hypothesis Testing by Betting
by: Sandoval, Ricardo J., et al.
Published: (2026)

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
by: Lau, Ivan, et al.
Published: (2025)

Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
by: Zhao, Yuxuan, et al.
Published: (2026)

Robust, Online, and Adaptive Decentralized Gaussian Processes
by: Llorente, Fernando, et al.
Published: (2025)

Singular Fluctuation as Specific Heat in Bayesian Learning
by: Plummer, Sean
Published: (2025)