Saved in:
| Main Authors: | Wang, Xiao, Borras, Hendrik, Klein, Bernhard, Fröning, Holger |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.16183 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On Hardening DNNs against Noisy Computations
by: Wang, Xiao, et al.
Published: (2025)
by: Wang, Xiao, et al.
Published: (2025)
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)
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)
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)
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles
by: Steger, Sophie, et al.
Published: (2024)
by: Steger, Sophie, 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)
Less Memory Means smaller GPUs: Backpropagation with Compressed Activations
by: Barley, Daniel, et al.
Published: (2024)
by: Barley, Daniel, et al.
Published: (2024)
Resource-Efficient and Robust Inference of Deep and Bayesian Neural Networks on Embedded and Analog Computing Platforms
by: Klein, Bernhard
Published: (2025)
by: Klein, Bernhard
Published: (2025)
How Controlling the Variance can Improve Training Stability of Sparsely Activated DNNs and CNNs
by: Dent, Emily, et al.
Published: (2026)
by: Dent, Emily, et al.
Published: (2026)
Resource-Efficient Neural Networks for Embedded Systems
by: Roth, Wolfgang, et al.
Published: (2020)
by: Roth, Wolfgang, et al.
Published: (2020)
Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments
by: Jin, Deliang, et al.
Published: (2025)
by: Jin, Deliang, 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)
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
by: Kwon, Young D., et al.
Published: (2023)
by: Kwon, Young D., et al.
Published: (2023)
Carbon Intensity-Aware Adaptive Inference of DNNs
by: Jung, Jiwan
Published: (2024)
by: Jung, Jiwan
Published: (2024)
Hessian-aware Training for Enhancing DNNs Resilience to Parameter Corruptions
by: Prato, Tahmid Hasan, et al.
Published: (2025)
by: Prato, Tahmid Hasan, et al.
Published: (2025)
Variance-Aware Adaptive Weighting for Diffusion Model Training
by: Sun, Nanlong, et al.
Published: (2026)
by: Sun, Nanlong, et al.
Published: (2026)
Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization
by: Eccles, Bailey J., et al.
Published: (2024)
by: Eccles, Bailey J., et al.
Published: (2024)
ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs
by: Mousavi, Seyedhamidreza, et al.
Published: (2024)
by: Mousavi, Seyedhamidreza, et al.
Published: (2024)
Denoising-Aware Contrastive Learning for Noisy Time Series
by: Zhou, Shuang, et al.
Published: (2024)
by: Zhou, Shuang, et al.
Published: (2024)
ReCycle: Resilient Training of Large DNNs using Pipeline Adaptation
by: Gandhi, Swapnil, et al.
Published: (2024)
by: Gandhi, Swapnil, et al.
Published: (2024)
TroLLoc: Logic Locking and Layout Hardening for IC Security Closure against Hardware Trojans
by: Wang, Fangzhou, et al.
Published: (2024)
by: Wang, Fangzhou, et al.
Published: (2024)
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
by: Fu, Shaopeng, et al.
Published: (2023)
by: Fu, Shaopeng, et al.
Published: (2023)
HAWX: A Hardware-Aware FrameWork for Fast and Scalable ApproXimation of DNNs
by: Nazari, Samira, et al.
Published: (2026)
by: Nazari, Samira, et al.
Published: (2026)
Koopman Theory-Inspired Method for Learning Time Advancement Operators in Unstable Flame Front Evolution
by: Yu, Rixin, et al.
Published: (2024)
by: Yu, Rixin, et al.
Published: (2024)
Complexity of One-Dimensional ReLU DNNs
by: Kogan, Jonathan, et al.
Published: (2025)
by: Kogan, Jonathan, et al.
Published: (2025)
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)
Towards Exact Gradient-based Training on Analog In-memory Computing
by: Wu, Zhaoxian, et al.
Published: (2024)
by: Wu, Zhaoxian, et al.
Published: (2024)
Mitigating Evasion Attacks in Fog Computing Resource Provisioning Through Proactive Hardening
by: Salmi, Younes, et al.
Published: (2026)
by: Salmi, Younes, et al.
Published: (2026)
Unstable Rankings in Bayesian Deep Learning Evaluation
by: Zhan, Qishi, et al.
Published: (2026)
by: Zhan, Qishi, et al.
Published: (2026)
On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
by: Schwalbe, Gesina, et al.
Published: (2025)
by: Schwalbe, Gesina, et al.
Published: (2025)
VASSO: Variance Suppression for Sharpness-Aware Minimization
by: Li, Bingcong, et al.
Published: (2025)
by: Li, Bingcong, et al.
Published: (2025)
ForeCal: Random Forest-based Calibration for DNNs
by: Nigam, Dhruv
Published: (2024)
by: Nigam, Dhruv
Published: (2024)
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?
by: Zhang, Kaiqi, et al.
Published: (2022)
by: Zhang, Kaiqi, et al.
Published: (2022)
Probabilistic Photonic Computing
by: Brückerhoff-Plückelmann, Frank, et al.
Published: (2026)
by: Brückerhoff-Plückelmann, Frank, et al.
Published: (2026)
CEAR: Certified Ensemble Adversarial Robustness in DNNs
by: Sadig, Daniel, et al.
Published: (2026)
by: Sadig, Daniel, et al.
Published: (2026)
Inverse Neural Operator for ODE Parameter Optimization
by: Liu, Zhi-Song, et al.
Published: (2026)
by: Liu, Zhi-Song, et al.
Published: (2026)
Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective
by: Wang, Jiancheng, et al.
Published: (2026)
by: Wang, Jiancheng, et al.
Published: (2026)
Uncertainty Reasoning with Photonic Bayesian Machines
by: Brückerhoff-Plückelmann, F., et al.
Published: (2025)
by: Brückerhoff-Plückelmann, F., et al.
Published: (2025)
Uncertainty-Aware Robust Learning on Noisy Graphs
by: Chen, Shuyi, et al.
Published: (2023)
by: Chen, Shuyi, et al.
Published: (2023)
Adversarial Resilience against Clean-Label Attacks in Realizable and Noisy Settings
by: Heinzler, Carolin
Published: (2025)
by: Heinzler, Carolin
Published: (2025)
Similar Items
-
On Hardening DNNs against Noisy Computations
by: Wang, Xiao, et al.
Published: (2025) -
Walking Noise: On Layer-Specific Robustness of Neural Architectures against Noisy Computations and Associated Characteristic Learning Dynamics
by: Borras, Hendrik, et al.
Published: (2022) -
Uncertainty-Preserving QBNNs: Multi-Level Quantization of SVI-Based Bayesian Neural Networks for Image Classification
by: Borras, Hendrik, et al.
Published: (2025) -
Accelerated Execution of Bayesian Neural Networks using a Single Probabilistic Forward Pass and Code Generation
by: Klein, Bernhard, et al.
Published: (2025) -
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles
by: Steger, Sophie, et al.
Published: (2024)