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Latest version: v1.5.3

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1.5.3

Changes
* Removed the hydra warning when using `lightly-serve`
* Improved the error messages and formatting of "well known" errors to improve the readability

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.2

Changes
* add benchmark results for MAE
* add timm version info to docs

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.1

Changes
* Refactor MAE to use TIMM VIT
* Add [AIM examples and docs](https://docs.lightly.ai/self-supervised-learning/examples/aim.html)
* Updated BYOL and MOCO [benchmarks](https://docs.lightly.ai/self-supervised-learning/getting_started/benchmarks.html)
* Use MMCRProjectionHead in examples

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.0

This release includes some breaking changes for users of [Lightly Worker](https://docs.lightly.ai/docs/install-lightly).

Breaking Changes
* Jobs are now scheduled with config v4 and require Lightly Worker 2.11 (breaking).

Changes
* Add mmcr projection head (thanks LukeSutor )
* Update argument type hints where the default is set to None to use Optional (thanks otavioon)
* Fix TiCoLoss (thanks guarin )
* Add timm version check
* fix parsing and caching issues with `lightly-serve`
* allow to use lightly behind a proxy by setting `HTTPS_PROXY` and `LIGHTLY_CA_CERTS`

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.4.26

Changes
* Add EMP-SSL Loss (thanks johnsutor).
* Add AIM Model from [Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf).
* Benchmark code is [here](https://github.com/lightly-ai/lightly/blob/master/benchmarks/imagenet/vitb16/aim.py).
* Documentation is coming soon!
* Add TiCo model code for ImageNet benchmark.
* Add examples and documentation for MMCR loss (thanks johnsutor).


Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.4.25

Changes
* Add MoCoV2 ImageNet benchmarks.
* Make KNN feature normalization optional.
* Implement W-MSE Loss and Transform (thanks johnsutor).
* Update generated specs with datasource expiration.

Models
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

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