Mohamad H. Danesh

According to our database, Mohamad H. Danesh authored at least 17 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Toward Hardware-Agnostic Quadrupedal World Models via Morphology Conditioning.

Mohamad H. Danesh, Chenhao Li, Amin Abyaneh, Anas El Houssaini, Kirsty Ellis, Glen Berseth, Marco Hutter, Hsiu-Chin Lin

CoRR, April, 2026

VOCALoco: Viability-Optimized Cost-Aware Adaptive Locomotion.

Stanley Wu, Mohamad H. Danesh, Simon Li, Hanna Yurchyk, Amin Abyaneh, Anas El Houssaini, David Meger, Hsiu-Chin Lin

IEEE Robotics Autom. Lett., February, 2026

Contractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations.

Amin Abyaneh, Charlotte Morissette, Mohamad H. Danesh, Anas El Houssaini, David Meger, Gregory Dudek, Hsiu-Chin Lin

CoRR, January, 2026

2025

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation.

Mohamad H. Danesh, Maxime Wabartha, Stanley Wu, Joelle Pineau, Hsiu-Chin Lin

CoRR, July, 2025

Learning to Coordinate with Experts.

Mohamad H. Danesh, Tu Trinh, Benjamin Plaut, Nguyen X. Khanh

CoRR, February, 2025

YRC-Bench: A Benchmark for Learning to Coordinate with Experts.

Mohamad H. Danesh, Khanh Xuan Nguyen, Tu Trinh, Benjamin Plaut

Trans. Mach. Learn. Res., 2025

2024

Getting By Goal Misgeneralization With a Little Help From a Mentor.

Tu Trinh, Mohamad H. Danesh, Nguyen X. Khanh, Benjamin Plaut

CoRR, 2024

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers, Yann Berthelot, Kinal Mehta, Dipam Chakraborty, Arjun KG, Valentin Charraut, Chang Ye, Zichen Liu, Lucas N. Alegre, Alexander Nikulin, Xiao Hu, Tianlin Liu, Jongwook Choi, Brent Yi

CoRR, 2024

Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions.

Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning.

Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2022

LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty.

Mohamad Hosein Danesh, Panpan Cai, David Hsu

Proceedings of the Conference on Robot Learning, 2022

2021

Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results.

Mohamad H. Danesh, Alan Fern

CoRR, 2021

Stochastic Block-ADMM for Training Deep Networks.

Saeed Khorram, Xiao Fu, Mohamad H. Danesh, Zhongang Qi, Fuxin Li

CoRR, 2021

Re-understanding Finite-State Representations of Recurrent Policy Networks.

Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram

Proceedings of the 38th International Conference on Machine Learning, 2021

Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract).

Mohamad H. Danesh

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Reducing Neural Network Parameter Initialization Into an SMT Problem.

Mohamad H. Danesh

CoRR, 2020

Understanding Finite-State Representations of Recurrent Policy Networks.

Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram

CoRR, 2020