PaTAS: A Framework for Trust Propagation in Neural Networks Using Subjective Logic
cs.AI, cs.LG
Submitted: 2025-11-25
Updated: 2026-10-03
Terminology
Sources
- SmoothGrad: removing noise by adding noise
- Dos and Don'ts of Machine Learning in Computer Security
- Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
- Weight Uncertainty in Neural Networks
- Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
- Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
- From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered
- Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
- Evidential Deep Learning to Quantify Classification Uncertainty
- Multi-Source Fusion Operations in Subjective Logic
- Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
- Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
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