אפשר לעיין בפוסטרים שיוצגו בכנס, דרך הקישורים הבאים:
- Adi Chowers and Micha Mandel – Modeling Detection Bias of Mobile Species
- Avner Kantor and Sheizaf Rafaeli – Modeling How Data Journalism Shapes Discussion Networks
- Dana Levin and Alon Kipnis – Guided Word Guessing with Language Models and Information-Theoretic Content Distillation
- Eilon Vaknin Laufer and Boaz Nadler – RGNMR: A Provable Algorithm for Robust Matrix Completion
- מיקי כסלו ורני שטרית – פונקציית ההסתברות המצטברת של התפלגות גמא מלמדת אותנו על הקשר בין ביקוש ומחיר
- Noam Tetelman and Daniel Nevo – Identifying Influential Individuals in a Causal Network Through Random Effects Framework
- Oren Yuval and Saharon Rosset – Cross Validation for Correlated Data in Classification Models
- Ron Sarafian, Dori Nissenbaum, Shira Raveh-Rubin and Yinon Rudich – Forecast and Classification of Dust Events in the East Mediterranean using Machine Learning
- Samuel Ackerman, Eitan Farchi, Orna Raz, and Assaf Toledo – Statistical multi-metric evaluation and visualization of LLM system predictive performance
- Tomer Meir, Uri Shalit, and Malka Gorfine – Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
- Matan Bendak and Yuval Benjamini – Random Intercepts in Ordinal Neural Networks
- Yotam Hadari, Michal Cohen-Shelly, Karin Sudri, Nitsan Halabi, Miriam Gibli, Roy Beigel, Sagit Benzekry, Rafael Kuperstein, Aias Masalha, Robert Klempfner, and Avi Sabbag – Deep Learning for ECG Screening of Moderate to Severe Aortic Valve Stenosis
- Yotam Hadari, Michal Cohen-Shelly, Karin Sudri, Nitsan Halabi, Miriam Gibli, Sagit Benzekry, Rafael Kuperstein, Aias Masalha, Robert Klempfner, Avi Sabbag – Deep Learning for ECG Screening of Moderate to Severe Tricuspid Valve Regurgitation
- Yotam Hadari, Michal Cohen-Shelly, Karin Sudri, Nitsan Halabi, Miriam Gibli, Sagit Benzekry, Rafael Kuperstein, Aias Masalha, Robert Klempfner, Avi Sabbag – Deep Learning for ECG Screening of Moderate to Severe Tricuspid Valve Regurgitation
