Implementations of various models for Text Classification in PyTorch.
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Updated
Nov 28, 2020 - Python
Implementations of various models for Text Classification in PyTorch.
Automatically generating language descriptions for remote sensing images has emerged as a significant research area within the field of remote sensing. This project focuses on attention-based captioning methods, which are a prominent class of deep learning-based techniques for generating captions.
Popular ML papers implementation.
👨🎨 DDPM, and High-Resolution Image Synthesis with Latent Diffusion Models, papers implementation from scratch using pytorch.
Personal implementation of the paper "A two-stage ensemble method for the detection of class-label noise"
Recommender System implementation using Tensorflow/Numpy
Re-implementation of the paper Deep Recurrent Attentive Writer (DRAW)
Pytorch implementation of DCGAN
BRTDP implemented including DS-MPI for upper bound
A PyTorch Implementation of Goodfellow et al.'s Paper on Generative Adversarial Networks
My Implementations' Archive
Self-Supervised Learning for OOD Detection (NeurIPS 2019)
X-Llama🦙 is an Extensible advanced language model framework, inspired by the original Llama model.
Implementation for the KCM-F-GH of the paper "Gaussian kernel c-means hard clustering algorithms with automated computation of the width hyper-parameters"
PyTorch implementation of "Effective dimension of machine learning models" paper
Latent diffusion model following Umar Jamil's tutorial https://youtu.be/ZBKpAp_6TGI?si=Fa822KYeOP_2LWdr https://github.com/hkproj/pytorch-stable-diffusion
This is a demo of the implementation of the program described in my Seminararbeit, a German paper typically written in 11th grade.
A Naive Tensorflow Implementation of "Phase-Based Active Contour" Model (PBAC)
Pytorch implementation of Yolov1
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