6159 Repositories
Python network-representation-learning Libraries
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).
Container : Context Aggregation Network
Container : Context Aggregation Network If you use this code for a paper please cite: @article{gao2021container, title={Container: Context Aggregati
An extremely simple, intuitive, hardware-friendly, and well-performing network structure for LiDAR semantic segmentation on 2D range image. IROS21
FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification.
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing
TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
Bunch of optimizer implementations in PyTorch
Bunch of optimizer implementations in PyTorch
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]
High capacity, high availability, well connected, fast lightning node.
LND ⚡ Routing High capacity, high availability, well connected, fast lightning node. We aim to become a top liquidity provider for the lightning netwo
A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".
RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
Adversarial Framework for (non-) Parametric Image Stylisation Mosaics
Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset
PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
WIT (Wikipedia-based Image Text) Dataset is a large multimodal multilingual dataset comprising 37M+ image-text sets with 11M+ unique images across 100+ languages.
WIT (Wikipedia-based Image Text) Dataset is a large multimodal multilingual dataset comprising 37M+ image-text sets with 11M+ unique images across 100+ languages.
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
Merlion: A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. I
MetaDrive: Composing Diverse Scenarios for Generalizable Reinforcement Learning
MetaDrive: Composing Diverse Driving Scenarios for Generalizable RL [ Documentation | Demo Video ] MetaDrive is a driving simulator with the following
An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"
Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
Labelling platform for text using distant supervision
With DataQA, you can label unstructured text documents using rule-based distant supervision.
Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)
Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co
[ICCV-2021] An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation
An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation (ICCV 2021) Introduction This is an official pytorch implemen
Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]
Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan
High level network definitions with pre-trained weights in TensorFlow
TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.
Library for fast text representation and classification.
fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T
Tensorforce: a TensorFlow library for applied reinforcement learning
Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp
Train a deep learning net with OpenStreetMap features and satellite imagery.
DeepOSM Classify roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. DeepOSM can: Download a chunk of
A best practice for tensorflow project template architecture.
A best practice for tensorflow project template architecture.
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
Introduction This is a PyTorch implementation of the following research papers: (1) Hierarchical Text Generation and Planning for Strategic Dialogue (
DeepLab resnet v2 model in pytorch
pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea
Image-to-Image Translation in PyTorch
CycleGAN and pix2pix in PyTorch New: Please check out contrastive-unpaired-translation (CUT), our new unpaired image-to-image translation model that e
Deep Reinforcement Learning with pytorch & visdom
Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A
Tree LSTM implementation in PyTorch
Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati
PyTorch implementation of Deformable Convolution
PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran
Fast Neural Style for Image Style Transform by Pytorch
FastNeuralStyle by Pytorch Fast Neural Style for Image Style Transform by Pytorch This is famous Fast Neural Style of Paper Perceptual Losses for Real
pytorch implementation of fast-neural-style
fast-neural-style 🌇 🚀 NOTICE: This codebase is no longer maintained, please use the codebase from pytorch examples repository available at pytorch/e
A PyTorch implementation of Learning to learn by gradient descent by gradient descent
Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST
Implementation of algorithms for continuous control (DDPG and NAF).
DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Implementation of Squeezenet in pytorch, pretrained models on Cifar 10 data to come
Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque
Reinforcement learning models in ViZDoom environment
DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p
A PyTorch implementation of DenseNet.
A PyTorch Implementation of DenseNet This is a PyTorch implementation of the DenseNet-BC architecture as described in the paper Densely Connected Conv
Sequence to Sequence Models with PyTorch
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.
AnimeGAN A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. Randomly Generated Images The images are
Highway networks implemented in PyTorch.
PyTorch Highway Networks Highway networks implemented in PyTorch. Just the MNIST example from PyTorch hacked to work with Highway layers. Todo Make th
Wide Residual Networks (WideResNets) in PyTorch
Wide Residual Networks (WideResNets) in PyTorch WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
Deep Q-Learning Network in pytorch (not actively maintained)
pytoch-dqn This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the followin
Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
DiscoGAN Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. Prerequisites Python 2.7
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM
A PyTorch Implementation of Single Shot MultiBox Detector
SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragom
Task-based end-to-end model learning in stochastic optimization
Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th
Time Delayed NN implemented in pytorch
Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN
Recurrent Variational Autoencoder that generates sequential data implemented with pytorch
Pytorch Recurrent Variational Autoencoder Model: This is the implementation of Samuel Bowman's Generating Sentences from a Continuous Space with Kim's
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
Realtime Multi-Person Pose Estimation By Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh. Introduction Code repo for winning 2016 MSCOCO Keypoints Cha
a pytorch implementation of auto-punctuation learned character by character
Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult
Fast Scattering Transform with CuPy/PyTorch
Announcement 11/18 This package is no longer supported. We have now released kymatio: http://www.kymat.io/ , https://github.com/kymatio/kymatio which
Official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT This repository is the official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification. ArXiv If
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Anchored CorEx: Hierarchical Topic Modeling with Minimal Domain Knowledge Correlation Explanation (CorEx) is a topic model that yields rich topics tha
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.
Multilingual Latent Dirichlet Allocation (LDA) Pipeline This project is for text clustering using the Latent Dirichlet Allocation (LDA) algorithm. It
The tool to make NLP datasets ready to use
chazutsu photo from Kaikado, traditional Japanese chazutsu maker chazutsu is the dataset downloader for NLP. import chazutsu r = chazutsu.data
Neural network models for joint POS tagging and dependency parsing (CoNLL 2017-2018)
Neural Network Models for Joint POS Tagging and Dependency Parsing Implementations of joint models for POS tagging and dependency parsing, as describe
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP
TextAttack 🐙 Generating adversarial examples for NLP models [TextAttack Documentation on ReadTheDocs] About • Setup • Usage • Design About TextAttack
Simplify stop motion animation with machine learning.
Simplify stop motion animation with machine learning.
Kornia is a open source differentiable computer vision library for PyTorch.
Open Source Differentiable Computer Vision Library
CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks
CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks
Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores
Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer
Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer This repository contains the PyTorch code for Evo-ViT. This work proposes a slow-fas
Efficient Sparse Attacks on Videos using Reinforcement Learning
EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her
Supervised Contrastive Learning for Downstream Optimized Sequence Representations
SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network
Learning based AI for playing multi-round Koi-Koi hanafuda card games. Have fun.
Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI
💛 Code and Dataset for our EMNLP 2021 paper: "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes"
Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes Official PyTorch implementation and EmoCause evaluatio
This repository contains code released by Google Research.
This repository contains code released by Google Research.
Pytorch Implementation of "Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation"
CRL_EGPG Pytorch Implementation of Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation We use contrastive loss implemented b
A collection of scripts to steal BTC from Lightning Network enabled custodial services. Only for educational purpose! Share your findings only when design flaws are fixed.
Lightning Network Fee Siphoning Attack LN-fee-siphoning is a collection of scripts to subtract BTC from Lightning Network enabled custodial services b
An flask app for fake image detector
fake_img_detector This is a ml based project: frameworks used:- Flask Google collab #Description: Here you can Upload two different looking image with
A collection of scripts to steal BTC from Lightning Network enabled custodial services. Only for educational purpose! Share your findings only when design flaws are fixed.
Lightning Network Fee Siphoning Attack LN-fee-siphoning is a collection of scripts to subtract BTC from Lightning Network enabled custodial services b
[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning [MedIA or Arxiv] and [Demo] This repository pr
TorchX: A PyTorch Extension Library for More Efficient Deep Learning
TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig
Netwalk is a Python library to discover, parse, analyze and change Cisco switched networks
Netwalk is a Python library born out of a large remadiation project aimed at making network device discovery and management as fast and painless as possible.
A collection of SOTA Image Classification Models in PyTorch
A collection of SOTA Image Classification Models in PyTorch
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR