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An object-aware diffusion model for generating chemical reactions
A modular framework for neural networks with Euclidean symmetry
List of Molecular and Material design using Generative AI and Deep Learning
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold N…
Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
Representation and learning framework for dynamic graphs using Graph Neural Networks.
QUICK: A GPU-enabled ab intio quantum chemistry software package
Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 2, and other large language models.
High-Resolution Image Synthesis with Latent Diffusion Models
Fully automated end-to-end framework to extract data from bar plots and other figures in scientific research papers using modules such as OpenCV, AWS-Rekognition.
Examples demonstrating how to reproduce the results in the paper.
Distributed PyTorch implementation of multi-headed graph convolutional neural networks
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Exabyte.io platform documentation containing a detailed explanation of the entities, and their relationship, as well as a list of hands-on video tutorials.
On-Device Training Under 256KB Memory [NeurIPS'22]
Hands-On Graph Neural Networks Using Python, published by Packt
A Graph Neural Network project on HIV data
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Productive, portable, and performant GPU programming in Python.
A 3D sparse LBM solver implemented using Taichi
3-D elastic material simulation with Taichi using the Material Point Method (MPM)
MPM-Py: A program for learning the Material Point Method using Python