Repository for my masters' thesis about adaptive pretraining on fact-checking tasks.

An overview of German transformer models related to language modeling in the field of Natural Language Processing.

Official Repository for The Paper, PianoBART: Symbolic Piano Music Understanding and Generating with Large-Scale Pre-Training

Cats or CAT Scans

This Repository contains an illustration of Object detection using a pre trained model of Yolov3 with the help of Coco dataset we could label the objects.

Fork of Official Implementation of Meta-Learning to Improve Pre-Training, NeurIPS'21 Poster. (https://arxiv.org/abs/2111.01754)

[NeurIPS 2022] DRAGON 🐲: Deep Bidirectional Language-Knowledge Graph Pretraining

Pretraining Techniques for Graph Transformers

Pretraining on 2015, 2019 and IDRIDs with ResNet 101 and 152 and fine tuning with 2019 dataset only

This is a flexible class for training specific layers of deep neural-nets in an online manner. Supports Keras models.

CMLM预训练的非官方实现

This repository contains a deep learning project focused on classifying fresh and rotten fruits using transfer learning, data augmentation, and fine-tuning techniques. The project utilizes a VGG16 base model pretrained on ImageNet and aims to achieve a validation accuracy of 92% or higher on a dataset comprising various fruit categories.

Improving Quality of Multilingual Question Answering and Cross-Lingual Transfer using Multitask Learning, Knowledge Distillation, and Data Augmentation

Implementation of sequence models and their applications in areas such as speech recognition, music synthesis, chatbots, machine translation, and more

Customized Pretraining for NLG Tasks

Predicting mutation effects based on deep mutational scanning data

Code for the paper: "Using Pre-training and Interaction Modeling for ancestry-specific disease prediction using multiomics data from the UK Biobank"

🎓Automatically Update CV Papers Daily using Github Actions (Update Every 24th hours)

Overview of self-supervised video representation learning methods.