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ar-pde-cnn

Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs

badam

das

DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations

deeponet

Learning nonlinear operators via DeepONet

deepritz

delfi

Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead

direct-preference-optimization

Reference implementation for DPO (Direct Preference Optimization)

domainbed

DomainBed is a suite to test domain generalization algorithms

fourier_neural_operator

Use Fourier transform to learn operators in differential equations.

gclmaster

graph-pde

Using graph network to solve PDEs

intro_dgm

An Introduction to Deep Generative Modeling: Examples

lfi

Neural likelihood-free methods in PyTorch.

llama-factory

Unify Efficient Fine-Tuning of 100+ LLMs

llm-cookbook

面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版

llxcode

moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

numberical_optimization

a numberical optimization lib base on numpy

orpo

Official repository for ORPO

pathomicfusion

Fusing Histology and Genomics via Deep Learning - IEEE TMI

pde-surrogate

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

simpo

SimPO: Simple Preference Optimization with a Reference-Free Reward

ssl_detection

Semi-supervised learning for object detection

torchkrnet

This is an unofficial implementation of the KRnet with Pytorch, which Tensorflow originally implemented.

towards-data-science-posts-notebooks

trl

Train transformer language models with reinforcement learning.

tsnpe_neurips

Code to reproduce results from `Truncated proposals for scalable and hassle-free simulation-based inference`

wan

A deep learning based method for solving high dimensional partial differential equations based on its weak form