Tightness Results for Local Consistency Relaxations in Continuous MRFs. - Yoav Wald; Amir Globerson (UAI, 2014)

Robust Conditional Probabilities. - Yoav Wald; Amir Globerson (NIPS, 2017)

Robust multitask Elliptical Regression (ROMER). - Nofar Noy; Yoav Wald; Gal Elidan; Ami Wiesel (CAMSAP, 2019)

Globally Optimal Learning for Structured Elliptical Losses. - Yoav Wald; Nofar Noy; Gal Elidan; Ami Wiesel (NeurIPS, 2019)

Explaining in Style: Training a GAN to explain a classifier in StyleSpace. - Oran Lang; Yossi Gandelsman; Michal Yarom; Yoav Wald; Gal Elidan; Avinatan Hassidim; William T. Freeman; Phillip Isola; Amir Globerson; Michal Irani; Inbar Mosseri (ICCV, 2021)

On Calibration and Out-of-Domain Generalization. - Yoav Wald; Amir Feder; Daniel Greenfeld; Uri Shalit (NeurIPS, 2021)

Optimizations Towards Robustness in Machine Learning. (כותר נוסף בעברית: אופטימיזציות לאמינות של מערכות לומדות). - Yoav Wald (2021)

In the Eye of the Beholder: Robust Prediction with Causal User Modeling. - Amir Feder; Guy Horowitz; Yoav Wald; Roi Reichart; Nir Rosenfeld (NeurIPS, 2022)

Malign Overfitting: Interpolation Can Provably Preclude Invariance. - Yoav Wald; Gal Yona; Uri Shalit; Yair Carmon (CoRR, 2022)

Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds. - Yoav Wald; Gal Yona; Uri Shalit; Yair Carmon (ICLR, 2023)

Causal-structure Driven Augmentations for Text OOD Generalization. - Amir Feder; Yoav Wald; Claudia Shi; Suchi Saria; David M. Blei (NeurIPS, 2023)

Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. - Aahlad Manas Puli; Lily H. Zhang; Yoav Wald; Rajesh Ranganath (NeurIPS, 2023)

Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection. - Yoav Wald; Suchi Saria (UAI, 2023)

Novel Node Category Detection Under Subpopulation Shift. - Hsing-Huan Chung; Shravan Chaudhari; Yoav Wald; Xing Han; Joydeep Ghosh (ECML/PKDD (4), 2024)

Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. - Aahlad Manas Puli; Nitish Joshi; Yoav Wald; He He 001; Rajesh Ranganath (Trans. Mach. Learn. Res., 2024)

Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift. - Gina Wong; Joshua Gleason; Rama Chellappa; Yoav Wald; Anqi Liu (Trans. Mach. Learn. Res., 2024)

Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do. - Yoav Wald; Mark Goldstein; Yonathan Efroni; Wouter A. C. van Amsterdam; Rajesh Ranganath (ICLR, 2025)

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. - Shalmali Joshi; Iñigo Urteaga; Wouter A. C. van Amsterdam; George Hripcsak; Pierre A. Elias; Benjamin R. C. Amor; Noémie Elhadad; James C. Fackler; Mark P. Sendak; Jenna Wiens; Kaivalya Deshpande; Yoav Wald; et al. (J. Am. Medical Informatics Assoc., 2025)

Between Linear and Sinusoidal: Rethinking the Time Encoder in Dynamic Graph Learning. - Hsing-Huan Chung; Shravan Chaudhari; Xing Han; Yoav Wald; Suchi Saria; Joydeep Ghosh (Trans. Mach. Learn. Res., 2025)