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The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
搜集、整理、发布 中文 自然语言处理 语料/数据集，与 有志之士 共同 促进 中文 自然语言处理 的 发展。
links to conference publications in graph-based deep learning
Bayesian optimization in PyTorch
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
InferSent sentence embeddings
Notebooks about Bayesian methods for machine learning
Gallery of OSMnx tutorials, usage examples, and feature demonstrations.
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Te…
Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/
Dual LSTM Encoder for Dialog Response Generation
A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
Therapeutics Commons (TDC): Multimodal Foundation for Therapeutic Science
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Ten thousand books, six million ratings
Cell2Sentence: Teaching Large Language Models the Language of Biology
Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations
semantic similarity framework for knowledge graph
A library for ML benchmarking. It's powerful.
PDFM Embeddings: location-based vectors for geo-spatial analysis.
Implementation of various topic models
Deep Learning and Logical Reasoning from Data and Knowledge
Graph Classification with Graph Convolutional Networks in PyTorch [NeurIPS 2018 Workshop]
Code for "Machine Learning for Physicists" lecture series by Florian Marquardt
Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
This is a lightweight web-interface for creating and sharing vector annotations over satellite/aerial imagery scenes.
A deep reinforcement learning (DRL) based approach for spatial layout of land use and roads in urban communities. (Nature Computational Science)
Multi-Graph Convolutional Neural Networks