Eulerian Paths with Regular Constraints. - Orna Kupferman; Gal Vardi (MFCS, 2016)

Flow Games. - Orna Kupferman; Gal Vardi; Moshe Y. Vardi (FSTTCS, 2017)

The Unfortunate-Flow Problem. - Orna Kupferman; Gal Vardi (ICALP, 2018)

Spanning-Tree Games. - Dan Hefetz; Orna Kupferman; Amir Lellouche; Gal Vardi (MFCS, 2018)

On relative and probabilistic finite counterability. - Orna Kupferman; Gal Vardi (Formal Methods Syst. Des., 2018)

Multi-player flow games. - Shibashis Guha; Orna Kupferman; Gal Vardi (Auton. Agents Multi Agent Syst., 2019)

Flow Logic. - Orna Kupferman; Gal Vardi (Log. Methods Comput. Sci., 2019)

Graph-Theoretic Problems from the Viewpoint of Formal Methods (כותר נוסף בעברית: בעיות בתורת הגרפים מנקודת המבט של אימות פורמלי). - Gal Vardi (2019)

Hardness of Learning Neural Networks with Natural Weights. - Amit Daniely; Gal Vardi (NeurIPS, 2020)

Neural Networks with Small Weights and Depth-Separation Barriers. - Gal Vardi; Ohad Shamir (Electron. Colloquium Comput. Complex., 2020)

From Local Pseudorandom Generators to Hardness of Learning. - Amit Daniely; Gal Vardi (COLT, 2021)

Size and Depth Separation in Approximating Benign Functions with Neural Networks. - Gal Vardi; Daniel Reichman 001; Toniann Pitassi; Ohad Shamir (COLT, 2021)

Implicit Regularization in ReLU Networks with the Square Loss. - Gal Vardi; Ohad Shamir (COLT, 2021)

Learning a Single Neuron with Bias Using Gradient Descent. - Gal Vardi; Gilad Yehudai; Ohad Shamir (NeurIPS, 2021)

Size and Depth Separation in Approximating Natural Functions with Neural Networks. - Gal Vardi; Daniel Reichman 001; Toniann Pitassi; Ohad Shamir (CoRR, 2021)

Width is Less Important than Depth in ReLU Neural Networks. - Gal Vardi; Gilad Yehudai; Ohad Shamir (COLT, 2022)

On the Optimal Memorization Power of ReLU Neural Networks. - Gal Vardi; Gilad Yehudai; Ohad Shamir (ICLR, 2022)

Reconstructing Training Data From Trained Neural Networks. - Niv Haim; Gal Vardi; Gilad Yehudai; Ohad Shamir; Michal Irani (NeurIPS, 2022)

On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. - Itay Safran; Gal Vardi; Jason D. Lee (NeurIPS, 2022)

The Sample Complexity of One-Hidden-Layer Neural Networks. - Gal Vardi; Ohad Shamir; Nati Srebro (NeurIPS, 2022)

On Margin Maximization in Linear and ReLU Networks. - Gal Vardi; Ohad Shamir; Nati Srebro (NeurIPS, 2022)

Gradient Methods Provably Converge to Non-Robust Networks. - Gal Vardi; Gilad Yehudai; Ohad Shamir (NeurIPS, 2022)

Implicit Regularization Towards Rank Minimization in ReLU Networks. - Nadav Timor; Gal Vardi; Ohad Shamir (ALT, 2023)

Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. - Spencer Frei; Gal Vardi; Peter L. Bartlett; Nathan Srebro (COLT, 2023)

Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. - Spencer Frei; Gal Vardi; Peter L. Bartlett; Nathan Srebro; Wei Hu (ICLR, 2023)

Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. - Gon Buzaglo; Niv Haim; Gilad Yehudai; Gal Vardi; Yakir Oz; Yaniv Nikankin; Michal Irani (NeurIPS, 2023)

Most Neural Networks Are Almost Learnable. - Amit Daniely; Nati Srebro; Gal Vardi (NeurIPS, 2023)

Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy. - Amit Daniely; Nati Srebro; Gal Vardi (NeurIPS, 2023)

The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. - Spencer Frei; Gal Vardi; Peter L. Bartlett; Nati Srebro (NeurIPS, 2023)

Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces. - Odelia Melamed; Gilad Yehudai; Gal Vardi (NeurIPS, 2023)

Efficiently Learning Neural Networks: What Assumptions May Suffice? - Amit Daniely; Nathan Srebro; Gal Vardi (CoRR, 2023)

Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds. - Odelia Melamed; Gilad Yehudai; Gal Vardi (CoRR, 2023)

Reconstructing Training Data from Multiclass Neural Networks. - Gon Buzaglo; Niv Haim; Gilad Yehudai; Gal Vardi; Michal Irani (CoRR, 2023)

On the Implicit Bias in Deep-Learning Algorithms. - Gal Vardi (Commun. ACM, 2023)

Noisy Interpolation Learning with Shallow Univariate ReLU Networks. - Nirmit Joshi; Gal Vardi; Nathan Srebro (ICLR, 2024)

Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. - Zhiwei Xu; Yutong Wang 002; Spencer Frei; Gal Vardi; Wei Hu (ICLR, 2024)

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. - Lijia Zhou; James B. Simon; Gal Vardi; Nathan Srebro (ICLR, 2024)

Provable Tempered Overfitting of Minimal Nets and Typical Nets. - Itamar Harel; William Hoza; Gal Vardi; Itay Evron; Nati Srebro; Daniel Soudry (NeurIPS, 2024)

Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality. - Marko Medvedev; Gal Vardi; Nati Srebro (NeurIPS, 2024)

Reconstructing Training Data From Real World Models Trained with Transfer Learning. - Yakir Oz; Gilad Yehudai; Gal Vardi; Itai Antebi; Michal Irani; Niv Haim (CoRR, 2024)

Approaching Deep Learning through the Spectral Dynamics of Weights. - David Yunis; Kumar Kshitij Patel; Samuel Wheeler; Pedro Savarese; Gal Vardi; Karen Livescu; Michael Maire; Matthew R. Walter (CoRR, 2024)

Provable Privacy Attacks on Trained Shallow Neural Networks. - Guy Smorodinsky; Gal Vardi; Itay Safran (CoRR, 2024)

Benign Overfitting in Single-Head Attention. - Roey Magen; Shuning Shang; Zhiwei Xu; Spencer Frei; Wei Hu; Gal Vardi (CoRR, 2024)

Perspective Games. - Orna Kupferman; Gal Vardi (ACM Trans. Comput. Log., 2024)

A Theory of Learning with Autoregressive Chain of Thought. - Nirmit Joshi; Gal Vardi; Adam Block; Surbhi Goel; Zhiyuan Li 005; Theodor Misiakiewicz; Nathan Srebro (COLT, 2025)

Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. - Nikolaos Tsilivis 002; Gal Vardi; Julia Kempe (ICLR, 2025)

Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context. - Spencer Frei; Gal Vardi (ICLR, 2025)

Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes. - Itamar Harel; Yonathan Wolanowsky; Gal Vardi; Nathan Srebro; Daniel Soudry (CoRR, 2025)