jamindy/ML-Papers-Explained

Explanation to key concepts in ML

ML Papers Explained

Explanations to key concepts in ML

Full Index

• BART
• BEiT
• BERT
• ConvMixer
• DistilBERT
• DiT
• Donut
• ERNIE-Layout
• Fast RCNN
• Faster RCNN
• Feature Pyramid Network
• Focal Loss (RetinaNet)
• Layout LM
• Layout LM v2
• Layout LM v3
• LiLT
• Masked Autoencoder
• MobileBERT
• RCNN
• SentenceBERT
• Swin Transformer
• TableNet
• TinyBERT
• Transformer
• Vision Transformer
• XLNet

By Category

RCNNs

• RCNN
• Fast RCNN
• Faster RCNN

Transformers

• BERT
• DistilBERT
• MobileBERT
• SentenceBERT
• TinyBERT
• Transformer
• XLNet

Layout Transformers

• ERNIE-Layout
• Layout LM
• Layout LM v2
• Layout LM v3
• LiLT

Document Information Processing

• TableNet
• DiT
• Donut

Vision Transformers

• BEiT
• Masked Autoencoder
• Swin Transformer
• Vision Transformer

Single Stage Object Detectors

• Feature Pyramid Network
• Focal Loss (RetinaNet)

---

Reach out to Ritvik or Elvis if you have any questions.

If you are interested to contribute, feel free to open a PR.

Join our Discord