SS2: Non-deterministic Deep Learning and Uncertainty Quantification
Tue, 9 Sep, 10:50 - 12:30 Italy Time (UTC +2)
Location: Utveggio
Session Type: Lecture
Session Chair: Ercan Kuruoglu, Institute of Data and Information
Track: Special Sessions
Tue, 9 Sep, 10:50 - 11:10 Italy Time (UTC +2)

SS2.1: Monte Carlo Functional Regularisation for Continual Learning
Pengcheng Hao, Menghao Zhu, Ercan Kuruoglu, Institute of Data and Information, China
Tue, 9 Sep, 11:10 - 11:30 Italy Time (UTC +2)

SS2.2: An Uncertainty Quantification Method Based on Evidence theory and Conformal Prediction
Rouaa Hoblos, Noura Dridi, Noureddine Zerhouni, Zeina Al Masry, Femto-st, France
Tue, 9 Sep, 11:30 - 11:50 Italy Time (UTC +2)

SS2.3: Trustworthy Prediction with Gaussian Process Knowledge Scores
Kurt Butler, The University of Edinburgh, United Kingdom; Guanchao Feng, Tong Chen, Petar Djuric, Stony Brook University, United States
Tue, 9 Sep, 11:50 - 12:10 Italy Time (UTC +2)

SS2.4: Uncertainty Quantification in Probabilistic Machine Learning Models: Theory, Methods, and Insights
Marzieh Ajirak, Cornell University, United States; Anand Ravishankar, Petar Djuric, Stony Brook University, United States
Tue, 9 Sep, 12:10 - 12:30 Italy Time (UTC +2)

SS2.5: RECURSIVE KALMANNET: DEEP LEARNING-AUGMENTED KALMAN FILTERING FOR STATE ESTIMATION WITH CONSISTENT UNCERTAINTY QUANTIFICATION
Hassan Mortada, Cyril Falcon, Yanis Kahil, Mathéo Clavaud, Jean-Philippe Michel, Exail, France