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Daniele Reda
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2020 – today
- 2024
- [c7]Setareh Cohan
, Guy Tevet
Flexible Motion In-betweening with Diffusion Models. SIGGRAPH (Conference Paper Track) 2024: 69 - [i9]Setareh Cohan, Guy Tevet, Daniele Reda, Xue Bin Peng, Michiel van de Panne:
Flexible Motion In-betweening with Diffusion Models. CoRR abs/2405.11126 (2024) - [i8]Guy Tevet, Sigal Raab, Setareh Cohan, Daniele Reda, Zhengyi Luo, Xue Bin Peng, Amit H. Bermano, Michiel van de Panne:
CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control. CoRR abs/2410.03441 (2024) - 2023
- [j1]Daniele Reda
Physics-based Motion Retargeting from Sparse Inputs. Proc. ACM Comput. Graph. Interact. Tech. 6(3): 33:1-33:19 (2023) - [c6]Alexis Jensen
Physical Simulation of Balance Recovery after a Push. MIG 2023: 23:1-23:11 - [i7]Daniele Reda, Jungdam Won, Yuting Ye, Michiel van de Panne, Alexander W. Winkler:
Physics-based Motion Retargeting from Sparse Inputs. CoRR abs/2307.01938 (2023) - 2022
- [c5]Daniele Reda, Hung Yu Ling, Michiel van de Panne:
Learning to Brachiate via Simplified Model Imitation. SIGGRAPH (Conference Paper Track) 2022: 24:1-24:9 - [i6]Tianxin Tao, Daniele Reda, Michiel van de Panne:
Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels. CoRR abs/2204.04905 (2022) - [i5]Daniele Reda, Hung Yu Ling, Michiel van de Panne:
Learning to Brachiate via Simplified Model Imitation. CoRR abs/2205.03943 (2022) - 2021
- [c4]Adam Scibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, Frank Wood:
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation. ITSC 2021: 720-725 - [i4]Adam Scibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, Frank Wood:
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation. CoRR abs/2104.11212 (2021) - 2020
- [c3]Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur
Urban Driving with Conditional Imitation Learning. ICRA 2020: 251-257 - [c2]Daniele Reda, Tianxin Tao, Michiel van de Panne:
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning. MIG 2020: 16:1-16:10 - [i3]Daniele Reda, Tianxin Tao, Michiel van de Panne:
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning. CoRR abs/2010.04304 (2020)
2010 – 2019
- 2019
- [c1]Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur
Learning to Drive in a Day. ICRA 2019: 8248-8254 - [i2]Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, Alex Kendall:
Urban Driving with Conditional Imitation Learning. CoRR abs/1912.00177 (2019) - 2018
- [i1]Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah:
Learning to Drive in a Day. CoRR abs/1807.00412 (2018)
Coauthor Index
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