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ORCIDMohamad H. Danesh
2020 – today
- 2025
[i10]Mohamad H. Danesh, Tu Trinh, Benjamin Plaut, Nguyen X. Khanh:
Learning to Coordinate with Experts. CoRR abs/2502.09583 (2025)- 2024
- [c5]Guy Azran
, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren:
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning. AAAI 2024: 10953-10961 - [c4]Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li:
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions. CVPR 2024: 7580-7590 - [i9]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:
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning. CoRR abs/2402.03046 (2024) - [i8]Saeed Khorram, Mingqi Jiang, Mohamad Shahbazi, Mohamad H. Danesh, Fuxin Li:
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions. CoRR abs/2402.17065 (2024) - [i7]Tu Trinh, Mohamad H. Danesh, Nguyen X. Khanh, Benjamin Plaut:
Getting By Goal Misgeneralization With a Little Help From a Mentor. CoRR abs/2410.21052 (2024) - 2023
- [i6]Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren:
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning. CoRR abs/2307.05209 (2023) - 2022
- [c3]Mohamad Hosein Danesh, Panpan Cai, David Hsu:
LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty. CoRL 2022: 199-211 - [i5]Mohamad H. Danesh, Panpan Cai, David Hsu:
LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty. CoRR abs/2209.11422 (2022) - 2021
- [c2]Mohamad H. Danesh:
Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract). AAAI 2021: 15775-15776 - [c1]Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram:
Re-understanding Finite-State Representations of Recurrent Policy Networks. ICML 2021: 2388-2397 - [i4]Saeed Khorram, Xiao Fu, Mohamad H. Danesh, Zhongang Qi, Fuxin Li:
Stochastic Block-ADMM for Training Deep Networks. CoRR abs/2105.00339 (2021) - [i3]Mohamad H. Danesh, Alan Fern:
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results. CoRR abs/2107.04982 (2021) - 2020
- [i2]Mohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram:
Understanding Finite-State Representations of Recurrent Policy Networks. CoRR abs/2006.03745 (2020) - [i1]Mohamad H. Danesh:
Reducing Neural Network Parameter Initialization Into an SMT Problem. CoRR abs/2011.01191 (2020)
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