Surface Networks via General Covers. - Niv Haim; Nimrod Segol; Heli Ben-Hamu; Haggai Maron; Yaron Lipman (ICCV, 2019)

Controlling Neural Level Sets. - Matan Atzmon; Niv Haim; Lior Yariv; Ofer Israelov; Haggai Maron; Yaron Lipman (NeurIPS, 2019)

Implicit Geometric Regularization for Learning Shapes. - Amos Gropp; Lior Yariv; Niv Haim; Matan Atzmon; Yaron Lipman (ICML, 2020)

From Discrete to Continuous Convolution Layers. - Assaf Shocher; Ben Feinstein; Niv Haim; Michal Irani (CoRR, 2020)

Diverse Generation from a Single Video Made Possible. - Niv Haim; Ben Feinstein; Niv Granot; Assaf Shocher; Shai Bagon; Tali Dekel; Michal Irani (ECCV (17), 2022)

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

Diverse Video Generation from a Single Video. - Niv Haim; Ben Feinstein; Niv Granot; Assaf Shocher; Shai Bagon; Tali Dekel; Michal Irani (CoRR, 2022)

SinFusion: Training Diffusion Models on a Single Image or Video. - Yaniv Nikankin; Niv Haim; Michal Irani (ICML, 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)

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

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)