This repo covers methodologies to utilize Pre Trained BERT model on NMT Task
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Updated
May 28, 2024 - Python
This repo covers methodologies to utilize Pre Trained BERT model on NMT Task
Simulations for the paper "Deep Learning for the Gaussian Wiretap Channel by Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder"
Pytorch implementation of FTNet for Semantic Segmentation on SODA, SCUT Seg, and MFN Datasets
University project, which goal is to build a system, that detects anomalies in CREDO dataset
Pytorch Image Captioning model using a CNN-RNN architecture
a dna sequence generation/classification using transformers
My implementation of autoencoders
MSc AI Thesis work - Depth Estimation for transparent objects
Vector-Quantized Generative Adversarial Networks
HTSM Masterwork
Apply deep learning model to generate text summaries in the form of short news articles using sequence to sequence (LSTM) model.
Invariant representation learning from imaging and spectral data
Interact with a trained chatbot that uses sequence to sequence model with luong attention mechanism over jointly trained encoder-decoder modules and implementation of greedy search decoding module.
Deep learning model to predict the normal flow between two consecutive frames, being the normal flow the projection of the optical flow on the gradient directions.
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Symbol Team model for PAN@AP 2023 shared task on Profiling Cryptocurrency Influencers with Few-shot Learning
Explore the world of large language models , featuring comprehensive source codes and guides on deploying them effectively in production environments
Learning cell communication from spatial graphs of cells
Experimental project for AI and NLP based on Transformer Architecture
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