Popular GitHub Repositories for Molecular Structure

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ???

Photogrammetric Computer Vision Framework

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212

Graphormer is a general-purpose deep learning backbone for molecular modeling.

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.

Interact, analyze and structure massive text, image, embedding, audio and video datasets

Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.

A deep learning package for many-body potential energy representation and molecular dynamics

[GenAI Application Development Framework] ? Build GenAI application quick and easy ? Easy to interact with GenAI agent in code using structure data and chained-calls syntax ? Use Agently Workflow to manage complex GenAI working logic ? Switch to any model without rewrite application code

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

Fast computer vision library for SFM, calibration, fiducials, tracking, image processing, and more.

Fast & Simple Resource-Constrained Learning of Deep Network Structure