Text Segmentation as a Supervised Learning Task. - Omri Koshorek; Adir Cohen; Noam Mor; Michael Rotman; Jonathan Berant (NAACL-HLT (2), 2018)

Detect the Unexpected: Novelty Detection in Large Astrophysical Surveys using Fisher Vectors. - Michael Rotman; Itamar Reis; Dovi Poznanski; Lior Wolf (KDIR, 2019)

Electric Analog Circuit Design with Hypernetworks And A Differential Simulator. - Michael Rotman; Lior Wolf (ICASSP, 2020)

A Novel Approach for Correcting Multiple Discrete Rigid In-Plane Motions Artefacts in MRI Scans. - Michael Rotman; Rafi Brada; Israel Beniaminy; Sangtae Ahn; Christopher J. Hardy; Lior Wolf (CoRR, 2020)

Shuffling Recurrent Neural Networks. - Michael Rotman; Lior Wolf (AAAI, 2021)

Natural Statistics Of Network Activations And Implications For Knowledge Distillation. - Michael Rotman; Lior Wolf (ICIP, 2021)

Effectively using unsupervised machine learning in next generation astronomical surveys. - Itamar Reis; Michael Rotman; Dovi Poznanski; J. Xavier Prochaska; Lior Wolf (Astron. Comput., 2021)

Unsupervised Disentanglement with Tensor Product Representations on the Torus. - Michael Rotman; Amit Dekel; Shir Gur; Yaron Oz; Lior Wolf (ICLR, 2022)

Energy Regularized RNNS for solving non-stationary Bandit problems. - Michael Rotman; Lior Wolf (ICASSP, 2023)

Gradient Adjusting Networks for Domain Inversion. - Erez Sheffi; Michael Rotman; Lior Wolf (SCIA (2), 2023)

Semi-supervised learning of partial differential operators and dynamical flows. - Michael Rotman; Amit Dekel; Ran Ilan Ber; Lior Wolf; Yaron Oz (UAI, 2023)