Mohamad H. Danesh

19 papers A* 4Journal 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Contractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations.
CoRR
Amin Abyaneh, Charlotte Morissette, Mohamad H. Danesh, Anas El Houssaini, David Meger, Gregory Dudek, Hsiu-Chin Lin
2026 J jnl
VOCALoco: Viability-Optimized Cost-Aware Adaptive Locomotion.
IEEE Robotics Autom. Lett.
Stanley Wu, Mohamad H. Danesh, Simon Li, Hanna Yurchyk, Amin Abyaneh, Anas El Houssaini, David Meger, Hsiu-Chin Lin
2025 J jnl
Learning to Coordinate with Experts.
CoRR
Mohamad H. Danesh, Tu Trinh, Benjamin Plaut, Nguyen X. Khanh
2025 J jnl
Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation.
CoRR
Mohamad H. Danesh, Maxime Wabartha, Stanley Wu, Joelle Pineau, Hsiu-Chin Lin
2025 J jnl
VOCALoco: Viability-Optimized Cost-aware Adaptive Locomotion.
CoRR
Stanley Wu, Mohamad H. Danesh, Simon Li, Hanna Yurchyk, Amin Abyaneh, Anas El Houssaini, David Meger, Hsiu-Chin Lin
2025 J jnl
YRC-Bench: A Benchmark for Learning to Coordinate with Experts.
Trans. Mach. Learn. Res.
Mohamad H. Danesh, Khanh Xuan Nguyen, Tu Trinh, Benjamin Plaut
2024 A* conf
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning.
AAAI
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
2024 J jnl
Getting By Goal Misgeneralization With a Little Help From a Mentor.
CoRR
Tu Trinh, Mohamad H. Danesh, Nguyen X. Khanh, Benjamin Plaut
2024 J jnl
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.
CoRR
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
2024 A* conf
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions.
CVPR
Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li
2024 J jnl
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions.
CoRR
Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li
2023 J jnl
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning.
CoRR
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
2022 J jnl
LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty.
CoRR
Mohamad H. Danesh, Panpan Cai, David Hsu
2021 J jnl
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results.
CoRR
Mohamad H. Danesh, Alan Fern
2021 A* conf
Re-understanding Finite-State Representations of Recurrent Policy Networks.
ICML
Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram
2021 A* conf
Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract).
AAAI
Mohamad H. Danesh
2021 J jnl
Stochastic Block-ADMM for Training Deep Networks.
CoRR
Saeed Khorram, Xiao Fu, Mohamad H. Danesh, Zhongang Qi, Fuxin Li
2020 J jnl
Reducing Neural Network Parameter Initialization Into an SMT Problem.
CoRR
Mohamad H. Danesh
2020 J jnl
Understanding Finite-State Representations of Recurrent Policy Networks.
CoRR
Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram