Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing
Fuente:
arXiv
Saved in:
| Main Authors: | Abdennadher, Yesmine, Garner, Philip N. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Convolutional Spiking-based GRU Cell for Spatio-temporal Data
by: Abdennadher, Yesmine, et al.
Published: (2025)
by: Abdennadher, Yesmine, et al.
Published: (2025)
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
by: He, Mutian, et al.
Published: (2024)
by: He, Mutian, et al.
Published: (2024)
There is a Singularity in the Loss Landscape
by: Lowell, Mark
Published: (2022)
by: Lowell, Mark
Published: (2022)
Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis
by: Chen, Jiaqing, et al.
Published: (2026)
by: Chen, Jiaqing, et al.
Published: (2026)
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
by: Ruhe, David, et al.
Published: (2019)
by: Ruhe, David, et al.
Published: (2019)
Visualizing Loss Functions as Topological Landscape Profiles
by: Geniesse, Caleb, et al.
Published: (2024)
by: Geniesse, Caleb, et al.
Published: (2024)
Model Merging on Loss Landscape: A Geometry Perspective
by: Lu, Juanwu, et al.
Published: (2026)
by: Lu, Juanwu, et al.
Published: (2026)
Evaluating Loss Landscapes from a Topology Perspective
by: Xie, Tiankai, et al.
Published: (2024)
by: Xie, Tiankai, et al.
Published: (2024)
Variational Inference via Smoothed Particle Hydrodynamics
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Early-Warning Signals of Grokking via Loss-Landscape Geometry
by: Xu, Yongzhong
Published: (2026)
by: Xu, Yongzhong
Published: (2026)
Matrix Sensing with Kernel Optimal Loss: Robustness and Optimization Landscape
by: Song, Xinyuan, et al.
Published: (2025)
by: Song, Xinyuan, et al.
Published: (2025)
Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
by: Zhong, Xuyang, et al.
Published: (2025)
by: Zhong, Xuyang, et al.
Published: (2025)
Identifying Sparsely Active Circuits Through Local Loss Landscape Decomposition
by: Chrisman, Brianna, et al.
Published: (2025)
by: Chrisman, Brianna, et al.
Published: (2025)
A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models
by: Xie, YuQing, et al.
Published: (2025)
by: Xie, YuQing, et al.
Published: (2025)
Be Bayesian by Attachments to Catch More Uncertainty
by: Shen, Shiyu, et al.
Published: (2023)
by: Shen, Shiyu, et al.
Published: (2023)
Practical Battery Health Monitoring using Uncertainty-Aware Bayesian Neural Network
by: Zhao, Yunyi, et al.
Published: (2024)
by: Zhao, Yunyi, et al.
Published: (2024)
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
by: Haimovich, Daniel, et al.
Published: (2023)
by: Haimovich, Daniel, et al.
Published: (2023)
Loss Landscape Degeneracy and Stagewise Development in Transformers
by: Hoogland, Jesse, et al.
Published: (2024)
by: Hoogland, Jesse, et al.
Published: (2024)
LightSNN: Lightweight Architecture Search for Sparse and Accurate Spiking Neural Networks
by: Abdennadher, Yesmine, et al.
Published: (2025)
by: Abdennadher, Yesmine, et al.
Published: (2025)
Collapsed Inference for Bayesian Deep Learning
by: Zeng, Zhe, et al.
Published: (2023)
by: Zeng, Zhe, et al.
Published: (2023)
Geometric Scaling of Bayesian Inference in LLMs
by: Agarwal, Naman, et al.
Published: (2025)
by: Agarwal, Naman, et al.
Published: (2025)
On Sequential Bayesian Inference for Continual Learning
by: Kessler, Samuel, et al.
Published: (2023)
by: Kessler, Samuel, et al.
Published: (2023)
Bayesian Inference of Training Dataset Membership
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Lightning Prediction under Uncertainty: DeepLight with Hazy Loss
by: Arifin, Md Sultanul, et al.
Published: (2025)
by: Arifin, Md Sultanul, et al.
Published: (2025)
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
by: Liang, Chen, et al.
Published: (2026)
by: Liang, Chen, et al.
Published: (2026)
Bayesian-Symbolic Integration for Uncertainty-Aware Parking Prediction
by: Nezhadettehad, Alireza, et al.
Published: (2026)
by: Nezhadettehad, Alireza, et al.
Published: (2026)
Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
by: Zhu, Yujie, et al.
Published: (2025)
by: Zhu, Yujie, et al.
Published: (2025)
Calibrated Test-Time Guidance for Bayesian Inference
by: Geyfman, Daniel, et al.
Published: (2026)
by: Geyfman, Daniel, et al.
Published: (2026)
Bayesian Inference for Correlated Human Experts and Classifiers
by: Kelly, Markelle, et al.
Published: (2025)
by: Kelly, Markelle, et al.
Published: (2025)
AI-Powered Bayesian Inference
by: O'Hagan, Sean, et al.
Published: (2025)
by: O'Hagan, Sean, et al.
Published: (2025)
Flat Channels to Infinity in Neural Loss Landscapes
by: Martinelli, Flavio, et al.
Published: (2025)
by: Martinelli, Flavio, et al.
Published: (2025)
Adapting Critic Match Loss Landscape Visualization to Off-policy Reinforcement Learning
by: Liu, Jingyi, et al.
Published: (2026)
by: Liu, Jingyi, et al.
Published: (2026)
VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR Identification
by: Wang, Pengyu, et al.
Published: (2025)
by: Wang, Pengyu, et al.
Published: (2025)
Loss Barcode: A Topological Measure of Escapability in Loss Landscapes
by: Barannikov, Serguei, et al.
Published: (2020)
by: Barannikov, Serguei, et al.
Published: (2020)
JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference
by: Bracher, Niels, et al.
Published: (2025)
by: Bracher, Niels, et al.
Published: (2025)
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification
by: Chen, Hui, et al.
Published: (2024)
by: Chen, Hui, et al.
Published: (2024)
Visualizing Critic Match Loss Landscapes for Interpretation of Online Reinforcement Learning Control Algorithms
by: Liu, Jingyi, et al.
Published: (2026)
by: Liu, Jingyi, et al.
Published: (2026)
A Loss Landscape Visualization Framework for Interpreting Reinforcement Learning: An ADHDP Case Study
by: Liu, Jingyi, et al.
Published: (2026)
by: Liu, Jingyi, et al.
Published: (2026)
Beyond Feature Fusion: Contextual Bayesian PEFT for Multimodal Uncertainty Estimation
by: Naderi, Habibeh, et al.
Published: (2026)
by: Naderi, Habibeh, et al.
Published: (2026)
Uncertainty Quantification of Large Language Models using Approximate Bayesian Computation
by: Sharma, Mridul, et al.
Published: (2025)
by: Sharma, Mridul, et al.
Published: (2025)
Similar Items
-
Convolutional Spiking-based GRU Cell for Spatio-temporal Data
by: Abdennadher, Yesmine, et al.
Published: (2025) -
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity
by: He, Mutian, et al.
Published: (2024) -
There is a Singularity in the Loss Landscape
by: Lowell, Mark
Published: (2022) -
Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis
by: Chen, Jiaqing, et al.
Published: (2026) -
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
by: Ruhe, David, et al.
Published: (2019)