Reading List
My reading list of research papers, articles, books and authors in Deep Learning, Natural Language Processing and Computer Vision.
Key:
- ✅ = Have read
- 👨🔬 = Have implemented
- ⏳ = Reading / Want to read
1. Research Papers and Articles
1.1. Natural Language Processing
Sequence-to-sequence
- ⏳ PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
- 👨🔬 PreSumm: Text Summarization with Pretrained Encoders
- ✅ BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
- ✅ T5: Text-To-Text Transfer Transformer
Transformers and Pretrained Language Models
- ⏳ Longformer: The Long-Document Transformer
- ⏳ Movement Pruning: Adaptive Sparsity by Fine-Tuning
- 👨🔬 MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
- 👨🔬 DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
- 👨🔬 ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
- 👨🔬 RoBERTa: A Robustly Optimized BERT Pretraining Approach
- 👨🔬 BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- ✅ The Illustrated Transformer
- ✅ Attention is All You Need
Sequence Classification
- 👨🔬 A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification
- 👨🔬 Convolutional Neural Networks for Sentence Classification
- ✅ Baselines and Bigrams
Word Embeddings
- ✅ Concatenated Power Mean Word Embeddings as Universal Cross-Lingual Sentence Representations
- ✅ Efficient Sentence Embedding using Discrete Cosine Transform
- ✅ FastText: Advances in Pre-Training Distributed Word Representations
- ✅ Word2vec: Efficient Estimation of Word Representations in Vector Space
1.2. Computer Vision
Object Detection and Semantic Segmentation
- ⏳ Detectron2
- ⏳ U-Net: Convolutional Networks for Biomedical Image Segmentation
- ⏳ Mask R-CNN
- ⏳ Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- ⏳ Fast R-CNN
Image Enhancing
Style Transfer
- ⏳ Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- 👨🔬 Image Style Transfer Using Convolutional Neural Networks
1.3. Others
- ⏳ Graph Neural Networks: A Review of Methods and Applications
- ⏳ Semi-Supervised Classification with Graph Convolutional Networks
- ✅ Deep Reinforcement Learning: Pong from Pixels
- 👨🔬 Generative_Adversarial_Networks