Popular GitHub Repositories for Alternate Energy

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

A deep learning package for many-body potential energy representation and molecular dynamics

"Deep Generative Modeling": Introductory Examples

(CVPR 2021 Oral) Open World Object Detection

Boltzmann Machines in TensorFlow with examples

List of Molecular and Material design using Generative AI and Deep Learning

Power Tools for AI Engineers With Deadlines

[ECCV 2022] Compositional Generation using Diffusion Models

Training neural network potentials

The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map

Explore the energy-efficient dataflow scheduling for neural networks.

OpenModelica Microgrid Gym (OMG): An OpenAI Gym Environment for Microgrids

? EcoLogits tracks the energy consumption and environmental footprint of using generative AI models through APIs.

Machine Learning for High Energy Physics.

Reinforcement learning for energy systems

Gym environment for building simulation and control using reinforcement learning

Deep Neural Networks Applied to Energy Disaggregation