Log Research Data

A simple program to calculate and visualize the FLOPs and Parameters of Pytorch models, with handy CLI and easy-to-use Python API.

Code for Neural Information Processing Systems (NeurIPS) 2019 paper: Pareto Multi-Task Learning

Automatic architecture search and hyperparameter optimization for PyTorch

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

An LLM-powered advanced RAG pipeline built from scratch

Scalable and user friendly neural 🧠 forecasting algorithms.

NeuralProphet: A simple forecasting package

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Fast and Accurate ML in 3 Lines of Code

Merlion: A Machine Learning Framework for Time Series Intelligence

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

Automated Time Series Forecasting

Night theme for Zotero UI and PDF

TCube generates rich and fluent narratives that describes the characteristics, trends, and anomalies of any time-series data (domain-agnostic) using the transfer learning capabilities of PLMs.

A large scale latent variable compartmental model for simulating abundance/population time series of interacting phages and microbes that undergoes lysis in presence of the phages.

This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

Neural relational inference for interacting systems - pytorch

ClaSPy: A Python package for time series segmentation.

This repository contains the time series segmentation benchmark (TSSB).

Database system for AI-powered apps

🛠️ Corrected Test Sets for ImageNet, MNIST, CIFAR, Caltech-256, QuickDraw, IMDB, Amazon Reviews, 20News, and AudioSet

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Code for paper 'Learning transferable cooperative behaviors in multi-agent teams' (ICML 2019)

Multi-Joint dynamics with Contact. A general purpose physics simulator.