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Implementation of Physics-Informed Diffusion Models
⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~
A simple implementaion of lattice Schwinger model in Julia
Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Learning Algebraic Multigrid Using Graph Neural Networks
Differentiable signal processing on the sphere for PyTorch
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
check code for common misspellings
DevOps Roadmap for 2025. with learning resources
A course in reinforcement learning in the wild
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
This repository contains the solutions and explanations to the algorithm problems on LeetCode. Only medium or above are included. All are written in C++/Python and implemented by myself. The proble…
List of Computer Science courses with video lectures.
Fast and Easy Infinite Neural Networks in Python
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
🎓 Path to a free self-taught education in Computer Science!
The code of a graph neural network (GNN) for molecules, which is based on learning representations of r-radius subgraphs (i.e., fingerprints) in molecules.
Implementation of Convolutional LSTM in PyTorch.
A (concise) curated list of awesome Causal Inference resources.
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Latex code for making neural networks diagrams