High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
Exposes information gathered from Proxmox VE cluster for use by the Prometheus monitoring system
In-Place Activated BatchNorm for Memory-Optimized Training of DNNs
[AAAI 2025]👔IMAGDressing👔: Interactive Modular Apparel Generation for Virtual Dressing. It enables customizable human image generation with flexible garment, pose, and scene control, ensuring high fidelity and garment consistency for virtual dressing.
A calendaring app for Django.
A simple toy demo of a local voice assistant with whisper and large language model.
Find unused, missing and transitive dependencies in a Python project.
[CVPR 2025 Highlight] Truncated Diffusion Model for Real-Time End-to-End Autonomous Driving
支持按轴凹总力战, 无缝制造三解, 用于实现蔚蓝档案自动化的程序( Steam已适配 )
Code to pretrain, fine-tune, and evaluate DreamZero and run sim & real-world evals
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.
