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Code for "Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?" [ICML 2023]

Cldr_clner_models ⭐ 23

Though language model text embeddings have revolutionized NLP research, their ability to capture high-level semantic information, such as relations between entities in text, is limited. In this paper, we propose a novel contrastive learning framework that trains sentence embeddings to encode the relations in a graph structure. Given a sentence (unstructured text) and its graph, we use contrastive learning to impose relation-related structure on the token level representations of the sentence obt

A simple tensor library for the computational graph on CPU

Paperlist ⭐ 22

report reading paper list

Open source machine learning for graph-structured data

Graphs In Machine Learning ⭐ 22

A curated list of resources on the intersection of Graphs and Machine Learning

A free, open-source inference and learning library for Sum-Product Networks (SPN)

Machine Learning Research Papers ⭐ 22

Collection of machine learning research paper references

Easy-to-use framework for graph continual learning with Python

Subgraph2vec_tf ⭐ 21

This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper

100daysofmlcodechallenge ⭐ 21

A repository dedicated to the #100DaysofMLCode Challenge.

Graph Cnn.mxnet ⭐ 20

MXNet implementation of Graph Convolutional Neural Networks

Gated Graph Transformers ⭐ 19

Transformers are Graph Neural Networks!

GEDFN: Graph-Embedded Deep Feedforward Network

TIP: Tri-graph Interaction Propagation model for Polypharmacy Side Eﬀect Prediction (GRL@NeurIPS, 2019)

FluidML is a lightweight framework for developing machine learning pipelines.

Model Alan ⭐ 18

对机器学习、概率图模型、主题模型领域一些模型进行实现，主要涉及一些近年高水平会议论文中提到的算法。

Neural Plot Development ⭐ 18

A Library for visualizing Neural Networks of the TensorFlow/Keras models.

dataflow graph\deep learning\async task

Deep Code Curation

Node Select ⭐ 17

NODE-SELECT: A Graph Neural Network Based On A Selective Propagation Technique

Naivenaslib.jl ⭐ 17

Relentless mutation!!

Deep Hyperedges ⭐ 17

New Algorithms for Learning on Hypergraphs

Resolutions 2019 ⭐ 16

A list of data mining and machine learning papers that I implemented in 2019.

A Python library for knowledge graph representation learning (graph embedding).

Ace Team Dlstudy ⭐ 15

Study materials about "Deep Learning for Molecular Applications".

Conditional Structure Generation through Graph Variational Generative Adversarial Nets, NeurIPS 2019.

Tensorflow Paper ⭐ 15

A review-paper on TensorFlow.

Graph2seq For Kgqg ⭐ 15

Code & data accompanying the paper "Toward Subgraph Guided Knowledge Graph Question Generation with Graph Neural Networks"

Molecule Attention Transformer ⭐ 15

Pytorch reimplementation of Molecule Attention Transformer, which uses a transformer to tackle the graph-like structure of molecules

Cosmopolitics ⭐ 15

Eurostat Big Data Hackathon 2021

DGL implementation of EGES

Recurrent Js ⭐ 14

[INACTIVE] Amazingly simple to build and train various neural networks. The library is an object-oriented neural network approach (baked with Typescript), containing stateless and stateful neural network architectures.

Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (code)

Graphsage_tf ⭐ 14

Tensorflow implementation of 'Inductive Representation Learning on Large Graphs'

Awesome Transfer Learning On Graph ⭐ 13

A curated paper list about transfer learning (mainly domain adaption) on graphs. Graph transfer learning (Graph domain adaption).

Differentia.js ⭐ 13

No longer being supported or maintained. A Graph Theory & Data Structure Library for JavaScript.

A deep learning library with static computational graph and auto-diff in C++.

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

Pytensor ⭐ 12

A numpy deep learning framework

Simp Gcn ⭐ 12

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Directed Graph Neural Network ⭐ 12

Dir-GNN is a machine learning model that enables learning on directed graphs.

Deep Learning ⭐ 12

This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

Nanograd ⭐ 12

A lightweight deep learning framework

Extended Simgnn ⭐ 11

A PyTorch Geometric implementation of SimGNN with some extensions.

Deep_learning ⭐ 11

projects about NLP knowledge graph, web crawling, word embedding, entity&relation extraction.

Wide And Deep ⭐ 11

Learning Paradigms For Tsp ⭐ 10

Code for the paper 'On Learning Paradigms for the Travelling Salesman Problem' (NeurIPS 2019 Graph Representation Learning Workshop)

Recurrent Graph Evolution Neural Network (ReGENN) using Graph Soft Evolution (GSE)

Pyscholargraph ⭐ 10

Code for "Five Hundred Deep Learning Papers, Graphviz and Python" (http://goo.gl/l1PIoi)

My Notebook ⭐ 10

Automatic differentiation in python

Implementation of ConvE proposed by Dettmers et al. in Convolutional 2D Knowledge Graph Embeddings.

Munglinker ⭐ 9

Experiments on Linking the Nodes of a Music Notation Graph (MuNG) with Deep Learning.

Neural Rdf Verbalizer ⭐ 9

🗣 Multilingual RDF Verbalizer – Google Summer of Code 2019

Ifmlab_gnn ⭐ 8

Graph Neural Network Models from IFM Lab

Pytorch Gnn Meta Attack ⭐ 8

Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.

Standalone Deeplearning Chemistry ⭐ 8

화학 분자를 딥러닝 아키텍쳐로 다루는 저장소입니다.

Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.

Ml_learning ⭐ 8

Fight for future.

Vgg Tensorflow ⭐ 8

VGGNet with TensorFlow

Keras implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation". Includes synthetic GED data.

Shortest Distance Approx Deep Learning ⭐ 8

Implementation of the paper "Shortest Path Distance Approximation using Deep learning Techniques" (under development)

Hullcoverconditionedunitdiskgraph ⭐ 8

A generator for unit disk graphs conditioned on concave hull cover.

Csci599 Deeplearning ⭐ 8

Kerasplotlib ⭐ 8

A visualization library for Keras deep learning

Treewidth Prediction ⭐ 8

Prediction of Treewidth using Graph Neural Network, developed as part of PFN summer internship 2019.

LEAP (Learning Edges by Aggregation of Paths)

Deep Learning For Vehicle License Detection

Awesome Graph Structure Learning ⭐ 8

A collection of research papers related to graph structure learning(GSL).

Noteobooks ⭐ 7

My notebooks about Deep Learning, Graph Processing and Other things!

Cifar10 Resnet Tensorflow ⭐ 7

base backbone model

Trackjectory ⭐ 7

Tracking and Trajectory Prediction

Template for projects in PyTorch powered with PyTorch Lightning, Telegrad and MLflow. Get updates on mobile and streamline PyTorch code for research.

This is the implementation and supplemental materials for paper "Deep Multi-attributed Graph Translation with Node-Edge Co-evolution"

Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".

Widedeepsequenceattentionframe ⭐ 7

Wide And Deep Sequence model Attention Mechanism

Sita: an synergic islets tracking architecture

Neural Machine Translation for RDFS reasoning: code and datasets for "Deep learning for noise-tolerant RDFS reasoning" http://www.semantic-web-journal.net/content/deep-l

Forestlayer ⭐ 7

ForestLayer: Efficient and scalable deep forest learning library based on Ray

Nns Meets Deep Rl ⭐ 7

Code for paper: Towards Similarity Graphs Constructed by Deep Reinforcement Learning

Pytorch_starter ⭐ 6

starter code for PyTorch with live graphs (visdom), progress bar (tqdm), flexible command line arguments

Vehicle Number Plate Detection ⭐ 6

This project demonstrates the use of TensorFlow Object Detection API to automatically number plates (Indian) from vehicles

Global Reasoned Multi Task Model ⭐ 6

PyTorch Implementation of "Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding" (ICRA '22, RA-L)

Unrolling of Deep Graph Total Variation for Image Denoising

Aprendizaje Geometrico ⭐ 6

Materiales del Curso Aprendizaje Geométrico Profundo, Posgrado Matemáticas UNAM 2023-1

Dynamic_graph_neural_network ⭐ 6

Clustering with dynamic neural network

Skeletongcn ⭐ 6

Skeleton Graph Convolution Network is based on the Deep Graph Library and inspired by ST-GCN network designing.

Python implementation of node2vec to generate node embeddings in a graph

A simple Java AI library for personal use.

Higher Order Graph Convolutional Neural Network ⭐ 6

A Tensorflow implementation of a higher order graph convolutional neural network

Official TensorFlow implementation for "Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol" [TIP 2021] and "Supervised Domain Adaptation using Graph Embedding" [ICPR 2020]

Mlinproduction ⭐ 6

Making Machine Learning easy in production

Cdt Ccm Aae ⭐ 6

Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds (2018, https://arxiv.org/abs/1805.06299)

Awesome Graph Networks ⭐ 6

Materials for Graph Models and Graph Networks

Torch_geometric_exploration ⭐ 6

Dlnlp Papernotes ⭐ 6

Summaries and notes on Deep Learning research papers in natural language processing(NLP) domain.

Deep Multi-Graph Clustering via Attentive Cross-Graph Association

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