Update README.md

Author: rwightman

README.md

@@ -346,6 +346,7 @@ Included optimizers available via `timm.optim.create_optimizer_v2` factory metho
 * `adafactorbv` adapted from [Big Vision](https://github.com/google-research/big_vision/blob/main/big_vision/optax.py) - https://arxiv.org/abs/2106.04560
 * `adahessian` by [David Samuel](https://github.com/davda54/ada-hessian) - https://arxiv.org/abs/2006.00719
 * `adamp` and `sgdp` by [Naver ClovAI](https://github.com/clovaai) - https://arxiv.org/abs/2006.08217
+* `adamuon` and `nadamuon` as per https://github.com/Chongjie-Si/AdaMuon - https://arxiv.org/abs/2507.11005
 * `adan` an implementation of Adan adapted from https://github.com/sail-sg/Adan - https://arxiv.org/abs/2208.06677
 * `adopt` ADOPT adapted from https://github.com/iShohei220/adopt - https://arxiv.org/abs/2411.02853
 * `kron` PSGD w/ Kronecker-factored preconditioner from https://github.com/evanatyourservice/kron_torch - https://sites.google.com/site/lixilinx/home/psgd
@@ -356,6 +357,7 @@ Included optimizers available via `timm.optim.create_optimizer_v2` factory metho
 * `lookahead` adapted from impl by [Liam](https://github.com/alphadl/lookahead.pytorch) - https://arxiv.org/abs/1907.08610
 * `madgrad` an implementation of MADGRAD adapted from https://github.com/facebookresearch/madgrad - https://arxiv.org/abs/2101.11075
 * `mars` MARS optimizer from https://github.com/AGI-Arena/MARS - https://arxiv.org/abs/2411.10438
+* `muon` MUON optimizer from https://github.com/KellerJordan/Muon with numerous additions and improved non-transformer behaviour
 * `nadam` an implementation of Adam w/ Nesterov momentum
 * `nadamw` an implementation of AdamW (Adam w/ decoupled weight-decay) w/ Nesterov momentum. A simplified impl based on https://github.com/mlcommons/algorithmic-efficiency
 * `novograd` by [Masashi Kimura](https://github.com/convergence-lab/novograd) - https://arxiv.org/abs/1905.11286
@@ -407,7 +409,7 @@ Several (less common) features that I often utilize in my projects are included.
      * [FAIRseq lr_scheduler](https://github.com/pytorch/fairseq/tree/master/fairseq/optim/lr_scheduler)
      * SGDR: Stochastic Gradient Descent with Warm Restarts (https://arxiv.org/abs/1608.03983)
   * Schedulers include `step`, `cosine` w/ restarts, `tanh` w/ restarts, `plateau`
-* Space-to-Depth by [mrT23](https://github.com/mrT23/TResNet/blob/master/src/models/tresnet/layers/space_to_depth.py) (https://arxiv.org/abs/1801.04590) -- original paper?
+* Space-to-Depth by [mrT23](https://github.com/mrT23/TResNet/blob/master/src/models/tresnet/layers/space_to_depth.py) (https://arxiv.org/abs/1801.04590)
 * Adaptive Gradient Clipping (https://arxiv.org/abs/2102.06171, https://github.com/deepmind/deepmind-research/tree/master/nfnets)
 * An extensive selection of channel and/or spatial attention modules:
     * Bottleneck Transformer - https://arxiv.org/abs/2101.11605