Akash Singh

About

I am a researcher in Machine Learning, with a particular focus on uncertainty quantification and its applications in decision-making systems. My work explores various uncertainty estimation methods, including ensemble-based approaches, Dempster-Shafer theory, and conformal prediction.
I am also interested in uncertainty-aware reinforcement learning models, and their role in improving reliable decision-making. My research spans probabilistic modeling, deep learning, and real-world applications of uncertainty estimation in ML systems.

Employment

• University of Liège PhD

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (4)

• Uncertainty-Aware Reinforcement Learning Agents for Noisy Environments
  2025 10th International Conference on Information Technology Trends (ITT) 2025 DOI: 10.1109/itt69610.2025.11352934
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• Deep Set Conditioned Latent Representations for Action Recognition
  Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, 2022 DOI: 10.48550/arXiv.2212.11030
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• Task Independent Capsule-Based Agents for Deep Q-Learning
  Artificial Intelligence and Machine Learning 2022 DOI: 10.1007/978-3-030-93842-0_4
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• Conformal Prediction: Calibrated Decision-Making
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