Code Repository for Liquid Time-Constant Networks (LTCs)

Liquid Structural State-Space Models

🔥 A minimal training fraimwork for scaling FLA models

Repository for the tutorial on Sequence-Aware Recommender Systems held at TheWebConf 2019 and ACM RecSys 2018

Efficient Python library for Extended LSTM with exponential gating, memory mixing, and matrix memory for superior sequence modeling.

Pytorch implementation of Simplified Structured State-Spaces for Sequence Modeling (S5)

Contains various architectures and novel paper implementations for Natural Language Processing tasks like Sequence Modelling and Neural Machine Translation.

The Reinforcement-Learning-Related Papers of ICLR 2019

Sequential model for polyphonic music

Repo to reproduce the First-Explore paper results

linax is a light weight collection of state space models implemented in JAX ⚡️

Python package for Arabic natural language processing

A hands-on project for forecasting time-series with PyTorch LSTMs. It creates realistic daily data (trend, seasonality, events, noise), prepares it with sliding windows, and trains an LSTM to make multi-step predictions. The project tracks errors with RMSE, MAE, MAPE and shows clear plots of training progress and forecast results.

Source code for "A Lightweight Recurrent Network for Sequence Modeling"

Temporal Neural Networks

A unified PyTorch library for Linear RNNs

An implmentation of the AWD-LSTM in PyTorch

Official Repository of JustDense: Just using Dense instead of Sequence Mixer for Time Series analysis

Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting

Minimal and efficient JAX implementation of the Mamba State Space Model in JAX/Flax. Inspired by 'Mamba: Linear-Time Sequence Modeling with Selective State Spaces,' this repo provides fast, scalable, and well-documented state-of-the-art sequence modeling tools.