Yoav Wald

31 papers A* 8A 2Journal 17Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.
J. Am. Medical Informatics Assoc.
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, Madalina Fiterau, Zachary C. Lipton, Daniel Malinsky, Madhur Nayan, Hongseok Namkoong, Soojin Park, Julia E. Vogt, Rajesh Ranganath
2025 J jnl
Active Slice Discovery in Large Language Models.
CoRR
Minhui Zhang, Prahar Ijner, Yoav Wald, Elliot Creager
2025 J jnl
Between Linear and Sinusoidal: Rethinking the Time Encoder in Dynamic Graph Learning.
CoRR
Hsing-Huan Chung, Shravan Chaudhari, Xing Han, Yoav Wald, Suchi Saria, Joydeep Ghosh
2025 J jnl
Between Linear and Sinusoidal: Rethinking the Time Encoder in Dynamic Graph Learning.
Trans. Mach. Learn. Res.
Hsing-Huan Chung, Shravan Chaudhari, Xing Han, Yoav Wald, Suchi Saria, Joydeep Ghosh
2025 J jnl
Open-Set Domain Adaptation Under Background Distribution Shift: Challenges and A Provably Efficient Solution.
CoRR
Shravan Chaudhari, Yoav Wald, Suchi Saria
2025 A* conf
Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do.
ICLR
Yoav Wald, Mark Goldstein, Yonathan Efroni, Wouter A. C. van Amsterdam, Rajesh Ranganath
2025 J jnl
Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do.
CoRR
Yoav Wald, Mark Goldstein, Yonathan Efroni, Wouter A. C. van Amsterdam, Rajesh Ranganath
2024 — conf
Novel Node Category Detection Under Subpopulation Shift.
ECML/PKDD (4)
Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh
2024 J jnl
Novel Node Category Detection Under Subpopulation Shift.
CoRR
Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh
2024 J jnl
Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation.
Trans. Mach. Learn. Res.
Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath
2024 J jnl
Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift.
CoRR
Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu
2024 J jnl
Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift.
Trans. Mach. Learn. Res.
Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu
2023 A conf
Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection.
UAI
Yoav Wald, Suchi Saria
2023 A* conf
Causal-structure Driven Augmentations for Text OOD Generalization.
NeurIPS
Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei
2023 J jnl
Causal-structure Driven Augmentations for Text OOD Generalization.
CoRR
Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei
2023 A* conf
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy.
NeurIPS
Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023 J jnl
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy.
CoRR
Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023 A* conf
Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds.
ICLR
Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon
2022 A* conf
In the Eye of the Beholder: Robust Prediction with Causal User Modeling.
NeurIPS
Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
2022 J jnl
In the Eye of the Beholder: Robust Prediction with Causal User Modeling.
CoRR
Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
2022 J jnl
Malign Overfitting: Interpolation Can Provably Preclude Invariance.
CoRR
Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon
2021 A* conf
Explaining in Style: Training a GAN to explain a classifier in StyleSpace.
ICCV
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
2021 J jnl
Explaining in Style: Training a GAN to explain a classifier in StyleSpace.
CoRR
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
2021 A* conf
On Calibration and Out-of-Domain Generalization.
NeurIPS
Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit
2021 J jnl
On Calibration and Out-of-domain Generalization.
CoRR
Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit
2021 — —
Optimizations Towards Robustness in Machine Learning. (כותר נוסף בעברית: אופטימיזציות לאמינות של מערכות לומדות).
Yoav Wald
2019 A* conf
Globally Optimal Learning for Structured Elliptical Losses.
NeurIPS
Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel
2019 — conf
Robust multitask Elliptical Regression (ROMER).
CAMSAP
Nofar Noy, Yoav Wald, Gal Elidan, Ami Wiesel
2017 — conf
Robust Conditional Probabilities.
NIPS
Yoav Wald, Amir Globerson
2017 J jnl
Robust Conditional Probabilities.
CoRR
Yoav Wald, Amir Globerson
2014 A conf
Tightness Results for Local Consistency Relaxations in Continuous MRFs.
UAI
Yoav Wald, Amir Globerson