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Papers I have read and/or implemented:

1)Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.98.146401

2)Cross-language framework for word recognition and spotting of Indic scripts
https://www.sciencedirect.com/science/article/pii/S0031320318300463#bib0020

3)U-Net: Convolutional Networks for Biomedical Image Segmentation
https://arxiv.org/abs/1505.04597

4)TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation
https://arxiv.org/abs/1801.05746

5)Feature Pyramid Networks for Object Detection
https://arxiv.org/abs/1612.03144

6)Focal Loss for Dense Object Detection
https://arxiv.org/abs/1708.02002

7)MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
https://arxiv.org/abs/1811.05660

8)BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://arxiv.org/abs/1810.04805

9)Attention Is All You Need
https://arxiv.org/abs/1706.03762

10)Single-Shot Refinement Neural Network for Object Detection
https://arxiv.org/abs/1711.06897

11)Automatic chemical design using a data-driven continuous representation of molecules
https://arxiv.org/abs/1610.02415

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