Formal Semantics and Verification of Network-Based Biocomputation Circuits. - Michelle Aluf-Medina; Till Korten; Avraham Raviv; Dan V. Nicolau Jr.; Hillel Kugler (VMCAI, 2021)

Layer Folding: Neural Network Depth Reduction using Activation Linearization. - Amir Ben Dror; Niv Zehngut; Avraham Raviv; Evgeny Artyomov; Ran Vitek; Roy J. Jevnisek (CoRR, 2021)

Layer Folding: Neural Network Depth Reduction using Activation Linearization. - Amir Ben Dror; Niv Zehngut; Avraham Raviv; Evgeny Artyomov; Ran Vitek (BMVC, 2022)

D-STEP: Dynamic Spatio-Temporal Pruning. - Avraham Raviv; Yonatan Dinai; Igor Drozdov; Niv Zehngut; Ishay Goldin (BMVC, 2022)

Prediction and Control of Stochastic Agents Using Formal Methods. - Avraham Raviv; Yuval Gerber; Liri Benzinou; Michelle Aluf-Medina; Hillel Kugler (FoMLAS@CAV, 2023)

Simulation and Verification of Network-Based Biocomputation Circuits. - Michelle Aluf-Medina; Avraham Raviv; Himanshu Arora; Till Korten; Hillel Kugler (ISCAS, 2023)

Learning Through Imitation by Using Formal Verification. - Avraham Raviv; Eliya Bronshtein; Or Reginiano; Michelle Aluf-Medina; Hillel Kugler (SOFSEM, 2023)

TAPS: Temporal Attention-Based Pruning and Scaling for Efficient Video Action Recognition. - Yonatan Dinai; Avraham Raviv; Nimrod Harel; Donghoon Kim; Ishay Goldin; Niv Zehngut (ACCV (3), 2024)

Formal Verification of Object Detection. - Avraham Raviv; Yizhak Yisrael Elboher; Michelle Aluf-Medina; Yael Leibovich Weiss; Omer Cohen; Roy Assa; Guy Katz; Hillel Kugler (CoRR, 2024)

Robust Deep Reinforcement Learning Using Formal Verification. - Avraham Raviv; Shaiel Vistuch; Boaz Gurevich; Erel Dekel; Hillel Kugler (TASE, 2025)