Saved in:
| Main Authors: | Steger, Sophie, Knoll, Christian, Klein, Bernhard, Fröning, Holger, Pernkopf, Franz |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.15758 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Accelerated Execution of Bayesian Neural Networks using a Single Probabilistic Forward Pass and Code Generation
by: Klein, Bernhard, et al.
Published: (2025)
by: Klein, Bernhard, et al.
Published: (2025)
Resource-Efficient Neural Networks for Embedded Systems
by: Roth, Wolfgang, et al.
Published: (2020)
by: Roth, Wolfgang, et al.
Published: (2020)
Self-Guided Belief Propagation -- A Homotopy Continuation Method
by: Knoll, Christian, et al.
Published: (2018)
by: Knoll, Christian, et al.
Published: (2018)
Walking Noise: On Layer-Specific Robustness of Neural Architectures against Noisy Computations and Associated Characteristic Learning Dynamics
by: Borras, Hendrik, et al.
Published: (2022)
by: Borras, Hendrik, et al.
Published: (2022)
On the Convexity and Reliability of the Bethe Free Energy Approximation
by: Leisenberger, Harald, et al.
Published: (2024)
by: Leisenberger, Harald, et al.
Published: (2024)
Uncertainty-Preserving QBNNs: Multi-Level Quantization of SVI-Based Bayesian Neural Networks for Image Classification
by: Borras, Hendrik, et al.
Published: (2025)
by: Borras, Hendrik, et al.
Published: (2025)
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
by: Toth, Christian, et al.
Published: (2024)
by: Toth, Christian, et al.
Published: (2024)
Variance-Aware Noisy Training: Hardening DNNs against Unstable Analog Computations
by: Wang, Xiao, et al.
Published: (2025)
by: Wang, Xiao, et al.
Published: (2025)
On Hardening DNNs against Noisy Computations
by: Wang, Xiao, et al.
Published: (2025)
by: Wang, Xiao, et al.
Published: (2025)
Adaptive Variational Inference in Probabilistic Graphical Models: Beyond Bethe, Tree-Reweighted, and Convex Free Energies
by: Leisenberger, Harald, et al.
Published: (2025)
by: Leisenberger, Harald, et al.
Published: (2025)
Less Memory Means smaller GPUs: Backpropagation with Compressed Activations
by: Barley, Daniel, et al.
Published: (2024)
by: Barley, Daniel, et al.
Published: (2024)
Angle-Equivariant Convolutional Neural Networks for Interference Mitigation in Automotive Radar
by: Oswald, Christian, et al.
Published: (2023)
by: Oswald, Christian, et al.
Published: (2023)
Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles
by: Shukla, Khemraj, et al.
Published: (2026)
by: Shukla, Khemraj, et al.
Published: (2026)
Lightweight and perceptually-guided voice conversion for electro-laryngeal speech
by: Mayrhofer, Benedikt, et al.
Published: (2026)
by: Mayrhofer, Benedikt, et al.
Published: (2026)
Is the Last Layer Sufficient for Uncertainty Quantification?
by: Wilson, Joseph, et al.
Published: (2026)
by: Wilson, Joseph, et al.
Published: (2026)
DeepHYDRA: Resource-Efficient Time-Series Anomaly Detection in Dynamically-Configured Systems
by: Stehle, Franz Kevin, et al.
Published: (2024)
by: Stehle, Franz Kevin, et al.
Published: (2024)
On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers
by: Dahary, Omer, et al.
Published: (2026)
by: Dahary, Omer, et al.
Published: (2026)
Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks
by: Pilar, Philipp, et al.
Published: (2025)
by: Pilar, Philipp, et al.
Published: (2025)
Multivariate Bayesian Last Layer for Regression with Uncertainty Quantification and Decomposition
by: Wang, Han, et al.
Published: (2024)
by: Wang, Han, 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)
Implications of Noise in Resistive Memory on Deep Neural Networks for Image Classification
by: Emonds, Yannick, et al.
Published: (2024)
by: Emonds, Yannick, et al.
Published: (2024)
A Tabular Schedule Abstraction for Communication-Aware Evaluation of Pipeline-Parallel LLM Training
by: Barley, Daniel, et al.
Published: (2026)
by: Barley, Daniel, et al.
Published: (2026)
Pathologies of Predictive Diversity in Deep Ensembles
by: Abe, Taiga, et al.
Published: (2023)
by: Abe, Taiga, et al.
Published: (2023)
Robustness of Explainable Artificial Intelligence in Industrial Process Modelling
by: Kantz, Benedikt, et al.
Published: (2024)
by: Kantz, Benedikt, et al.
Published: (2024)
FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference
by: Feng, Qian, et al.
Published: (2024)
by: Feng, Qian, et al.
Published: (2024)
Evaluating Prediction Uncertainty Estimates from BatchEnsemble
by: Blørstad, Morten, et al.
Published: (2026)
by: Blørstad, Morten, et al.
Published: (2026)
Transitional Uncertainty with Layered Intermediate Predictions
by: Benkert, Ryan, et al.
Published: (2024)
by: Benkert, Ryan, et al.
Published: (2024)
Bayesian Optimization via Continual Variational Last Layer Training
by: Brunzema, Paul, et al.
Published: (2024)
by: Brunzema, Paul, et al.
Published: (2024)
Predicting gene essentiality and drug response from perturbation screens in preclinical cancer models with LEAP: Layered Ensemble of Autoencoders and Predictors
by: Bodinier, Barbara, et al.
Published: (2025)
by: Bodinier, Barbara, et al.
Published: (2025)
Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification
by: Franzen, Courtney, et al.
Published: (2026)
by: Franzen, Courtney, et al.
Published: (2026)
Closed-Form Last Layer Optimization
by: Galashov, Alexandre, et al.
Published: (2025)
by: Galashov, Alexandre, et al.
Published: (2025)
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights
by: Ahmed, Soyed Tuhin, et al.
Published: (2024)
by: Ahmed, Soyed Tuhin, et al.
Published: (2024)
Last Layer Empirical Bayes
by: Villecroze, Valentin, et al.
Published: (2025)
by: Villecroze, Valentin, et al.
Published: (2025)
Feature Repulsion and Spectral Lock-in: An Empirical Study of Two-Layer Network Grokking
by: Xu, Yongzhong
Published: (2026)
by: Xu, Yongzhong
Published: (2026)
Supervised Learning via Ensembles of Diverse Functional Representations: the Functional Voting Classifier
by: Riccio, Donato, et al.
Published: (2024)
by: Riccio, Donato, et al.
Published: (2024)
Stochasticity in Tokenisation Improves Robustness
by: Steger, Sophie, et al.
Published: (2026)
by: Steger, Sophie, et al.
Published: (2026)
Identifying Drivers of Predictive Aleatoric Uncertainty
by: Iversen, Pascal, et al.
Published: (2023)
by: Iversen, Pascal, et al.
Published: (2023)
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
by: Sarmiento, Paulo Yanez, et al.
Published: (2024)
by: Sarmiento, Paulo Yanez, et al.
Published: (2024)
Uncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles
by: Zhai, Yuanzhao, et al.
Published: (2023)
by: Zhai, Yuanzhao, et al.
Published: (2023)
On Multiangle Discrete Fractional Periodic Transforms
by: Oswald, Christian, et al.
Published: (2025)
by: Oswald, Christian, et al.
Published: (2025)
Similar Items
-
Accelerated Execution of Bayesian Neural Networks using a Single Probabilistic Forward Pass and Code Generation
by: Klein, Bernhard, et al.
Published: (2025) -
Resource-Efficient Neural Networks for Embedded Systems
by: Roth, Wolfgang, et al.
Published: (2020) -
Self-Guided Belief Propagation -- A Homotopy Continuation Method
by: Knoll, Christian, et al.
Published: (2018) -
Walking Noise: On Layer-Specific Robustness of Neural Architectures against Noisy Computations and Associated Characteristic Learning Dynamics
by: Borras, Hendrik, et al.
Published: (2022) -
On the Convexity and Reliability of the Bethe Free Energy Approximation
by: Leisenberger, Harald, et al.
Published: (2024)