Popular GitHub Repositories for Minimum

[ICLR 2025] Official implementation of Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration

Minimum-distortion embedding with PyTorch

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch

Light version of convolutional neural network Yolo v3 & v2 for objects detection with a minimum of dependencies (INT8-inference, BIT1-XNOR-inference)

SphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

This is the minimum implementation demo of ChatPDF, which answers related questions about PDF.

A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

Fast finetuning using a booster model that puts the initial state to a local minimum

LLM steganography with minimum-entropy coupling - Hiding encrypted messages in natural language.

This Repository Contains Solution to the Assignments of the Natural Language Processing Specialization from Deeplearning.ai on Coursera Taught by Younes Bensouda Mourri, ?ukasz Kaiser, Eddy Shyu

Computes the MWER (minimum WER) Loss with CTC beam search. Knowledge distillation for CTC loss.

OpenAI/ChatGPT library for Java - Requires JDK 11 at minimum.

Knowledge Graph summarization for anomaly/error detection & completion (WebConf '20)

A basic ui for running gpt neo 2.7B on low vram (3 gb Vram minimum)

[CVPR'25 Highlight] The official implementation of "GG-SSMs: Graph-Generating State Space Models"

A Minimum Control Program (MCP) server implementation for web browsing capabilities using BeautifulSoup4

Optimized loss based on cross-entropy (CE), like MWER (minimum WER) Loss with beam search and negative sampling strategy, Smoothed Max Pooling Loss.

Deep learning-based topology optimization with a minimum compliance loss function

This repo contains implementations of some of the classical computer vision algorithms/techniques for feature extraction, feature matching, image transformation, color image reconstruction, image denoising, image classification, and image segmentation.