Axel Brando

Orcid: 0000-0001-8103-391X

According to our database1, Axel Brando authored at least 24 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Probing the Embedding Space of Transformers via Minimal Token Perturbations.
CoRR, June, 2025

Seeing the Unseen: How EMoE Unveils Bias in Text-to-Image Diffusion Models.
CoRR, May, 2025

Object detection in adverse weather conditions for autonomous vehicles using Instruct Pix2Pix.
CoRR, May, 2025

Semantic Diverse DMR and TMR for High-Integrity AI-Based Function Efficiency.
ACM Trans. Cyber Phys. Syst., April, 2025

Leveraging Image-Based Transformations to Mitigate Adversarial Attacks in AI-Based Safety-Critical Systems.
Proceedings of the 31st IEEE International Symposium on On-Line Testing and Robust System Design, 2025

Managing Sources of Uncertainty in Utilizing AI in Development and Deployment of Safety-Critical Autonomous Systems.
Proceedings of the 22nd IEEE International Conference on Software Architecture, 2025

2024
GPU Implementation of Semantic Diverse DMR and TMR for High-Integrity AI-Based Functionalities.
Dataset, June, 2024

Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models.
Proceedings of the Uncertainty in Artificial Intelligence, 2024

Safety-Relevant AI-Based System Robustification with Neural Network Ensembles.
Proceedings of the 30th IEEE International Symposium on On-Line Testing and Robust System Design, 2024

2023
Main sources of variability and non-determinism in AD software: taxonomy and prospects to handle them.
Real Time Syst., September, 2023

On Neural Networks Redundancy and Diversity for Their Use in Safety-Critical Systems.
Computer, May, 2023

Contextual dataset from a Public Service Media.
Dataset, April, 2023

NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS.
CoRR, 2023



Retrospective Uncertainties for Deep Models using Vine Copulas.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Standardizing the Probabilistic Sources of Uncertainty for the sake of Safety Deep Learning.
Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022
Aleatoric Uncertainty Modelling in Regression Problems using Deep Learning
PhD thesis, 2022

Using Quantile Regression in Neural Networks for Contention Prediction in Multicore Processors.
Proceedings of the 34th Euromicro Conference on Real-Time Systems, 2022

Deep Non-crossing Quantiles through the Partial Derivative.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020
Building Uncertainty Models on Top of Black-Box Predictive APIs.
IEEE Access, 2020

2019
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Uncertainty Estimation for Black-Box Classification Models: A Use Case for Sentiment Analysis.
Proceedings of the Pattern Recognition and Image Analysis - 9th Iberian Conference, 2019

2018
Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy Series.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018


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