| Students |
Matriculation Numbers |
Area Assigned |
Assigned Paper |
| 1. Megha Maria Akash |
7046896 |
5 |
Truthful Elicitation of Imprecise Forecasts, UAI 2025 |
| 2. Monseej Purkayastha |
7047530 |
4 |
Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty? UAI, 2023 |
| 3. Ali El Chami |
7032017 |
7 |
Random-Set Large Language Models, ArXiv 2025 |
| 4. Bartlomiej Pogodzinski |
7028213 |
6 |
Decision Making under Uncertainty using Imprecise Probabilities, IJAR, 2007 |
| 5. Shao Yun Guo |
7039430 |
4 |
Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison, UAI 2022 |
| 6. Maurice Kunzler |
2580747 |
2 |
Learning Sets of Probabilities Through Ensemble Methods, ECSQARU 2023 |
| 7. Kanav Avasthi |
7063504 |
7 |
Credal Self-Supervised Learning, NeurIPS, 2021 |
| 8. Ali Kanso |
7014138 |
6 |
Archimedean Choice Functions: An Axiomatic Foundation for Imprecise Decision Making, IPMUKBS 2020 |
| 9. Parham Yazdkhasti |
7047838 |
1 |
Credal Learning Theory, NeurIPS 2024 |
| 10. Ali Zindari |
7048032 |
2 |
Neural Network Model for Imprecise Regression with Interval Dependent Variables, Neural Networks, 2023 |
| 11. Joseph Shiels |
7068792 |
4 |
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation, NeurIPS 2022 |
| 12. Yigit Yalin |
7072407 |
1 |
Towards a strictly frequentist theory of imprecise probability, ISIPTA 2023 |
| 13. Shahkriyor Khoshimov |
7069413 |
3 |
Conformalized Credal Set Predictors, NeurIPS, 2024 |
| 14. Huyen Vo |
7073034 |
3 |
Conformal Prediction Regions are Imprecise Highest Density Regions, ArXiv, 2025 |
| 15. Senjuti Dutta |
7043728 |
3 |
Learning Calibrated Belief Functions from Conformal Predictions, ISIPTA, 2023 |
| 16. Georgi Vitanov |
7025852 |
5 |
On the Calibration of Probabilistic Classifier Sets, AISTATS, 2023 |
