[CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone

Factored inference for discrete-continuous smoothing and mapping.

Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer IEEE JBHI https://ieeexplore.ieee.org/document/10006398

A high-performance, extensible aircraft GNC framework for Julia

The repository gives case studies on short-term traffic flow forecasting strategies within the scope of my master thesis.

Official repo for AMD hybrid models training and inference workflow

Hybrid ML models for thermodynamic property prediction

Monte Carlo simulation for financial instruments.

Ancestral sequence reconstruction using generative models

COCALITE: A Hybrid Model COmbining CAtch22 and LITE for Time Series Classification

Using Gaussian Processes for Deep Neural Network Predictive Uncertainty Estimation

Source code for the paper "HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting".

Production-grade ensemble framework combining XGBoost, PyTorch & Sklearn - 70%+ test coverage with Optuna optimization for time-series prediction

Time Series Forecasting using Linear Regression, Trend, Seasonality, Hybrid models

A robust movie recommendation system using the MovieLens dataset, employing Collaborative Filtering, Matrix Factorization, and Hybrid Models to enhance recommendation accuracy and diversity.

This repository enables training Ultralytics object detection models with the anchor-free LADA assignment algorithm and DFL-based regression. Multi-model feature fusion, joint training, and hybrid inference are also supported.

Run modern hybrid/MoE LLMs correctly and fast on cheap old Tesla P100 / GTX 1080 Ti cards. Fork of ik_llama.cpp: clean concurrent (np>1) Gated-DeltaNet hybrid decoding + Pascal sm_60 FP16 build tuning + built-in fan-out decomposer.

A minimal hybrid Quantum–Graph Neural Network prototype

Final semester research paper analyzing Quantum CNNs vs. ResNet-50 for medical image classification, developed under deadline pressure using AI-assisted coding tools and neural architecture optimizers. Submitted as coursework to demonstrate quantum-classical hybrid vs. traditional CNN efficacy in diagnostic imaging.

In my code portfolio, I generally try new techniques and methods in machine learning. I don't like only copying and pasting.