Direct Validation of the Information Bottleneck Principle for Deep Nets. - Adar Elad; Doron Haviv; Yochai Blau; Tomer Michaeli (ICCV Workshops, 2019)

Understanding and Controlling Memory in Recurrent Neural Networks. - Doron Haviv; Alexander Rivkind; Omri Barak (ICML, 2019)

The Ramanujan Machine: Automatically Generated Conjectures on Fundamental Constants. - Gal Raayoni; George Pisha; Yahel Manor; Uri Mendlovic; Doron Haviv; Yaron Hadad; Ido Kaminer (CoRR, 2019)

Generating conjectures on fundamental constants with the Ramanujan Machine. - Gal Raayoni; Shahar Gottlieb; Yahel Manor; George Pisha; Yoav Harris; Uri Mendlovic; Doron Haviv; Yaron Hadad; Ido Kaminer (Nat., 2021)

Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping. - Russell Z. Kunes; Mingzhang Yin; Max Land; Doron Haviv; Dana Pe'er; Simon Tavaré (AAAI, 2023)

scKINETICS: inference of regulatory velocity with single-cell transcriptomics data. - Cassandra Burdziak; Chujun Julia Zhao; Doron Haviv; Direna Alonso-Curbelo; Scott W. Lowe; Dana Pe'er (Bioinform., 2023)

Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer. - Doron Haviv; Russell Zhang Kunes; Thomas Dougherty; Cassandra Burdziak; Tal Nawy; Anna Gilbert; Dana Pe'er (ICML, 2024)

Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers. - Doron Haviv; Russell Zhang Kunes; Thomas Dougherty; Cassandra Burdziak; Tal Nawy; Anna Gilbert; Dana Pe'er (CoRR, 2024)

Wasserstein Flow Matching: Generative modeling over families of distributions. - Doron Haviv; Aram-Alexandre Pooladian; Dana Pe'er; Brandon Amos (CoRR, 2024)