hybrid-models

[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

Official repo for AMD hybrid models training and inference workflow

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

Hybrid ML models for thermodynamic property prediction

Ancestral sequence reconstruction using generative models

Monte Carlo simulation for financial instruments.

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

Using Gaussian Processes for Deep Neural Network Predictive Uncertainty Estimation

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

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".

Separating the attention and recurrent memory channels of hybrid language models

Stateful local LLM inference manager with persistent KV-cache, native filesystem tools, and instant undo: built in C++ on llama.cpp

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.

Hybrid LSTM-XGBoost model for stock return prediction and portfolio optimization with backtesting and Explainable AI.

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.