
## Acknowledgement
We thank the authors of the following projects, which provide great support during the development of our repository. 


* [TorchCFM, Tong et al.](https://github.com/atong01/conditional-flow-matching): Conditional flow-matching repository.
* [Shortcut Models, Francs et al.](https://github.com/kvfrans/shortcut-models): One-step Diffusion via Shortcut Models. 
* [DPPO, Ren et al.](https://github.com/irom-princeton/dppo):  DPPO official implementation. Authors include [Allen Z. Ren](https://allenzren.github.io/), [Justin Lidard](https://jlidard.github.io/), [Lars L. Ankile](https://ankile.com/), [Anthony Simeonov](https://anthonysimeonov.github.io/) [Pulkit Agrawal](https://people.csail.mit.edu/pulkitag/), [Anirudha Majumdar](https://mae.princeton.edu/people/faculty/majumdar), [Benjamin Burchfiel](http://www.benburchfiel.com/), [Hongkai Dai](https://hongkai-dai.github.io/), [Max Simchowitz](https://msimchowitz.github.io/). 
* [mujoco-2.1-rl-project, cubrink](https://github.com/cubrink/mujoco-2.1-rl-project#): training a Humanoid-v3 agent with SAC
* [Robomimic, Mandlekar et al.](https://github.com/ARISE-Initiative/robomimic): Robomimic benchmark
* [Diffuser, Janner et al.](https://github.com/jannerm/diffuser): general code base and DDPM implementation
* [Diffusion Policy, Chi et al.](https://github.com/real-stanford/diffusion_policy): general code base especially the env wrappers
* [CleanRL, Huang et al.](https://github.com/vwxyzjn/cleanrl): PPO implementation
* [IBRL, Hu et al.](https://github.com/hengyuan-hu/ibrl): ViT implementation
* [D3IL, Jia et al.](https://github.com/ALRhub/d3il): D3IL benchmark
* [Furniture-Bench, Heo et al.](https://github.com/clvrai/furniture-bench): Furniture-Bench benchmark
* [AWR, Peng et al.](https://github.com/xbpeng/awr): DAWR baseline (modified from AWR)
* [DIPO, Yang et al.](https://github.com/BellmanTimeHut/DIPO): DIPO baseline
* [IDQL, Hansen-Estruch et al.](https://github.com/philippe-eecs/IDQL): IDQL baseline
* [DQL, Wang et al.](https://github.com/Zhendong-Wang/Diffusion-Policies-for-Offline-RL): DQL baseline
* [QSM, Psenka et al.](https://www.michaelpsenka.io/qsm/): QSM baseline
* [Score SDE, Song et al.](https://github.com/yang-song/score_sde_pytorch/): diffusion exact likelihood