Code Repository for Liquid Time-Constant Networks (LTCs)

Liquid Structural State-Space Models

Live-bending a foundation model’s output at neural network level.

This repository hosts a stock market prediction model for Tesla and Apple using Liquid Neural Networks. It showcases data-driven forecasting techniques, feature engineering, and machine learning to enhance the accuracy of financial predictions.

Liquid Neural Networks (LNNs) Classification, Clustering, and Regression

Liquid Time-constant Networks implementation with PyTorch

Code repository for Liquid Time-stochasticity networks (LTSs)

LIQUID NEURAL NETWORK LNN CLASSIFIER AND REGRESSION

Code repository for "Efficiently Capturing Causality in Data with Liquid Time-Constant Neural Networks" Master's Thesis

Amazon SageMaker algorithm for time series forecasting with liquid neural networks (LNNs).

Predict Steering angles given Road Videos using liquid neural networks, ConvLSTMs and 3D Convolutions

A Liquid RL framework for Autonomous Cyber Defence

Evolutionary optimization of liquid neural networks

🌊 Develop innovative liquid structural state-space models for accurate estimation of health metrics like SpO2, heart rate, and speech recognition.

📈 Predict Tesla stock movements using machine learning with regression and classification models, backed by detailed data analysis and visualization.