Ryukijano

-Transformers-

Implementations of different Transformers on a variety of problems.

All-In-For-Students-Graduation-2023

ANIME_DF_GAN

Custom trained GAN Model in Pytorch to create completely random Deep Fake Images of Anime Characters from human characters

Deep-Reinforcement-Learning-and-Hugging-Face

ESRGAN_AND_YOLOV7

Implementation for the final year project and the paper Improved Pothole Detection Using ESRGAN and YOLOv7

Graph-Neural-Networks-

Implementations of popular Graph Neural Network models in PyTorch/TensorFlow/Jax

JAXploration

Dive deep into the world of Machine Learning with the JAX framework! 🚀 This repository houses my learning journey, experiments, and implementations of cutting-edge papers and projects using JAX. Join me as I unravel the power and flexibility of JAX in ML! 🧠💡

PyTorch-Differentiable-Stochastic-Differential-Equations

Implementations using torchSDE library from Google Research.

Pytorch-Vision-Transformer

Vision Transformer implemented from scratch in Pytorch

Self.Diffusion

Python scripts or notebooks of different implementation of small scale diffusion networks for prototyping and then experimented with different datasets.

Ryukijano/Self.Diffusion

Python scripts or notebooks of different implementation of small scale diffusion networks for prototyping and then experimented with different datasets.

Ryukijano/ESRGAN_AND_YOLOV7

Implementation for the final year project and the paper Improved Pothole Detection Using ESRGAN and YOLOv7

Ryukijano/-Transformers-

Implementations of different Transformers on a variety of problems.

Ryukijano/Deep-Reinforcement-Learning-and-Hugging-Face

Ryukijano/DL_audio

An audio classifier implemented in Pytorch using a CNN model with 3 layers.

Ryukijano/OPEN_GL_Graphics_Programming

This repository contains the OpenGL programs and builds I made.

Ryukijano/Qiskit_on_Qubit

Ryukijano/Ryukijano

Ryukijano/cudawesome

A collection of awesome algorithms, implemented in CUDA.

Ryukijano/Graph-Neural-Networks-

Implementations of popular Graph Neural Network models in PyTorch/TensorFlow/Jax

Ryukijano/JAXploration

Dive deep into the world of Machine Learning with the JAX framework! 🚀 This repository houses my learning journey, experiments, and implementations of cutting-edge papers and projects using JAX. Join me as I unravel the power and flexibility of JAX in ML! 🧠💡

Ryukijano/audio-diffusion

Apply diffusion models using the new Hugging Face diffusers package to synthesize music instead of images.

Ryukijano/bitsandbytes

8-bit CUDA functions for PyTorch

Ryukijano/CatCon-Controlnet-WD-1-5-b2

Experimental proof of concept made for the [Huggingface JAX/Diffusers community sprint](https://github.com/huggingface/community-events/tree/main/jax-controlnet-sprint)

Ryukijano/CCassesment

Ryukijano/cicd_forml_test

Learning how to create ci-cd tests for ml

Ryukijano/Gradio_app_scripts_notebooks

Scripts and notebooks for gradio apps for huggingface spaces.

Ryukijano/graph-ml-web-app.github.io

Ryukijano/IF

Deep Floyd IF

Ryukijano/makeavid-sd-tpu

Ryukijano/Mojo-jojo

This repository is dedicated to my learning journey with the Mojo language. It contains a collection of programs written in Mojo as I explore its syntax, semantics, and capabilities. Whether you’re a fellow learner or an experienced Mojo programmer, feel free to explore, contribute, and provide feedback. Let’s master Mojo together

Ryukijano/Physics-Based-DeepLearning

Dedicated to exploring the intersection of physics and machine learning.

Ryukijano/Programming_for_data_science_project

OWO UWU. What are you guys looking for?

Ryukijano/Pytorch_3d_ryu

Work in progress.

Ryukijano/Pytorch_xla

tutorial_notebooks and pytorch self implementations done on the tpu.

Ryukijano/r2d2

Implementation of R2D2 algorithm

Ryukijano/Ryukijano.github.io

Ryukijano/sleap

A deep learning framework for multi-animal pose tracking.

Ryukijano/SoulsGym

OpenAI gym extension for DarkSouls III

Ryukijano/tapnet

TAPIR is a two-stage algorithm which employs two stages: 1) a matching stage, which independently locates a suitable candidate point match for the query pointon every other frame, and (2) a refinement stage, which updates both the trajectory and query features based on local correlations. The resulting model is fast and surpasses all prior methods