Popular GitHub Repositories for Charge Transport

POT : Python Optimal Transport

TorchCFM: a Conditional Flow Matching library

Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.

[NeurIPS 2024] GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

Neural Light Transport for Relighting and View Synthesis

PyTorch implementation of "Neural Optimal Transport" (ICLR 2023 Spotlight)

[CVPR 2022 Oral] Marginal Correspondence for Conditional Image Generation, [CVPR 2021] Unbalanced Feature Transport for Exemplar-based Image Translation

MCPOmni Connect is a versatile command-line interface (CLI) client designed to connect to various Model Context Protocol (MCP) servers using both stdio and sse transport. It provides seamless integration with OpenAI models and all other LLM and supports dynamic tool and resource management across multiple servers.

[ICLR2023] PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

A collection of Nerual Network Models for chemistry

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging EVs under various disturbances (weather conditions, pricing models, stochastic arrival-departure EV times and stochastic Battery State of Charge (BOC) at arrival). This is an open source OpenAI Gym environment for the implementation of Reinforcement Learning (RL), Rule-based approaches (RB) and Intelligent Control (IC).

Async transport layers for MCP

Implementation of the Sliced Wasserstein Autoencoder using PyTorch

Анализ трафика на круговом движении с использованием компьютерного зрения

The official repository for the paper "Optimal Flow Matching: Learning Straight Trajectories in Just One Step" (NeurIPS 2024)

Regression Graph Neural Network (regGNN) for cognitive score prediction.

A graph neural network for the prediction of bond dissociation energies for molecules of any charge.