7921 Repositories
Python Deep-Learning-Models-for-Network-Annomaly-Detection Libraries
Fit models to your data in Python with Sherpa.
Table of Contents Sherpa License How To Install Sherpa Using Anaconda Using pip Building from source History Release History Sherpa Sherpa is a modeli
labsecurity is a framework and its use is for ethical hacking and computer security
labsecurity labsecurity is a framework and its use is for ethical hacking and computer security. Warning This tool is only for educational purpose. If
Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
Codes-for-Algorithms Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
Using pytorch to implement unet network for liver image segmentation.
Using pytorch to implement unet network for liver image segmentation.
Offline Multi-Agent Reinforcement Learning Implementations: Solving Overcooked Game with Data-Driven Method
Overcooked-AI We suppose to apply traditional offline reinforcement learning technique to multi-agent algorithm. In this repository, we implemented be
Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework
This repo is the official implementation of "Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework". @inproceedings{zhou2021insta
A simple Neural Network that predicts the label for a series of handwritten digits
Neural_Network A simple Neural Network that predicts the label for a series of handwritten numbers This program tries to predict the label (1,2,3 etc.
Multi-task Learning of Order-Consistent Causal Graphs (NeuRIPs 2021)
Multi-task Learning of Order-Consistent Causal Graphs (NeuRIPs 2021) Authors: Xinshi Chen, Haoran Sun, Caleb Ellington, Eric Xing, Le Song Link to pap
Flow is a computational framework for deep RL and control experiments for traffic microsimulation.
Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap
Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding
2D-TAN (Optimized) Introduction This is an optimized re-implementation repository for AAAI'2020 paper: Learning 2D Temporal Localization Networks for
Contextual speed detection for python
Speed Prediction using Optical Flow and 2D CNN About the challenge: Comma.AI Speed Challenge This challenge was developed by Comma.AI to predict the s
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: WavLM (arXiv): WavLM: Large-Scale Self-Supervised Pre-training for Full Stack Speech Processing UniSpeech (ICML 202
This repository contains the code, models and datasets discussed in our paper "Few-Shot Question Answering by Pretraining Span Selection"
Splinter This repository contains the code, models and datasets discussed in our paper "Few-Shot Question Answering by Pretraining Span Selection", to
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow.
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow. Documentation Proper documentation is available at
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
ByT5: Towards a token-free future with pre-trained byte-to-byte models
ByT5: Towards a token-free future with pre-trained byte-to-byte models ByT5 is a tokenizer-free extension of the mT5 model. Instead of using a subword
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation
CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener
Edge-Augmented Graph Transformer
Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:
FastFormers - highly efficient transformer models for NLU
FastFormers FastFormers provides a set of recipes and methods to achieve highly efficient inference of Transformer models for Natural Language Underst
Repo for Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization
ESACL: Enhanced Seq2Seq Autoencoder via Contrastive Learning for AbstractiveText Summarization This repo is for our paper "Enhanced Seq2Seq Autoencode
The code for the Subformer, from the EMNLP 2021 Findings paper: "Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers", by Machel Reid, Edison Marrese-Taylor, and Yutaka Matsuo
Subformer This repository contains the code for the Subformer. To help overcome this we propose the Subformer, allowing us to retain performance while
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models
PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised
Fine-tuning scripts for evaluating transformer-based models on KLEJ benchmark.
The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.
Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the
Large-scale pretraining for dialogue
A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT) This repository contains the source code and trained model for a large-
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
DeLighT: Very Deep and Light-Weight Transformers
DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (I
Fully featured implementation of Routing Transformer
Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the
DeBERTa: Decoding-enhanced BERT with Disentangled Attention
DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using
This repository contains the code for running the character-level Sandwich Transformers from our ACL 2020 paper on Improving Transformer Models by Reordering their Sublayers.
Improving Transformer Models by Reordering their Sublayers This repository contains the code for running the character-level Sandwich Transformers fro
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020
Code for the paper "Language Models are Unsupervised Multitask Learners"
Status: Archive (code is provided as-is, no updates expected) gpt-2 Code and models from the paper "Language Models are Unsupervised Multitask Learner
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
GPT Neo 🎉 1T or bust my dudes 🎉 An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here t
Awesome Treasure of Transformers Models Collection
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].
CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req
Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch.
AWS RoseTTAFold Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch. Overview Proteins are large biomolecules that play
This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev
MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F
Using VapourSynth with super resolution models and speeding them up with TensorRT.
VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi
A curated list of long-tailed recognition resources.
Awesome Long-tailed Recognition A curated list of long-tailed recognition and related resources. Please feel free to pull requests or open an issue to
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui
Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data
FTLNet_Pytorch Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data 1. Introduction This repo is an unofficial
Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting" by Shu et al.
[Re] Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. CVPR 2018
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Tensorflow code and models for the paper: Large Scale Fine-Grained Categ
Code for paper "Learning to Reweight Examples for Robust Deep Learning"
learning-to-reweight-examples Code for paper Learning to Reweight Examples for Robust Deep Learning. [arxiv] Environment We tested the code on tensorf
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th
A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》
RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai
Adjust Decision Boundary for Class Imbalanced Learning
Adjusting Decision Boundary for Class Imbalanced Learning This repository is the official PyTorch implementation of WVN-RS, introduced in Adjusting De
[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"
DRAGON: From Generalized zero-shot learning to long-tail with class descriptors Paper Project Website Video Overview DRAGON learns to correct the bias
Face and Body Tracking for VRM 3D models on the web.
Kalidoface 3D - Face and Full-Body tracking for Vtubing on the web! A sequal to Kalidoface which supports Live2D avatars, Kalidoface 3D is a web app t
Deep learning for Engineers - Physics Informed Deep Learning
SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki
DeepCourse: Deep Learning for Computer Vision arthurdouillard.com/deepcourse/ This is a course I'm giving to the French engineering school EPITA each
Continual World is a benchmark for continual reinforcement learning
Continual World Continual World is a benchmark for continual reinforcement learning. It contains realistic robotic tasks which come from MetaWorld. Th
Deep Learning Theory
Deep Learning Theory 整理了一些深度学习的理论相关内容,持续更新。 Overview Recent advances in deep learning theory 总结了目前深度学习理论研究的六个方向的一些结果,概述型,没做深入探讨(2021)。 1.1 complexity
PyContinual (An Easy and Extendible Framework for Continual Learning)
PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read
The implementation of Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
INSTA: Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning This repository provides the implementation and demo of Learning Instanc
Implementation of Research Paper "Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation"
Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E
Automated Evidence Collection for Fake News Detection
Automated Evidence Collection for Fake News Detection This is the code repo for the Automated Evidence Collection for Fake News Detection paper accept
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.
Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D)
Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D) Code & Data Appendix for Conjugated Discrete Distributions for Distr
Cognition-aware Cognate Detection
Cognition-aware Cognate Detection The repository which contains our code for our EACL 2021 paper titled, "Cognition-aware Cognate Detection". This wor
Multi-task yolov5 with detection and segmentation based on yolov5
YOLOv5DS Multi-task yolov5 with detection and segmentation based on yolov5(branch v6.0) decoupled head anchor free segmentation head README中文 Ablation
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset
关于实现的一点说明 山东大学 2020级 苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数: resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a,返回一个$lenb\times lenb$的方阵。因
MARS: Learning Modality-Agnostic Representation for Scalable Cross-media Retrieva
Introduction This is the source code of our TCSVT 2021 paper "MARS: Learning Modality-Agnostic Representation for Scalable Cross-media Retrieval". Ple
Manipulation OpenAI Gym environments to simulate robots at the STARS lab
Manipulator Learning This repository contains a set of manipulation environments that are compatible with OpenAI Gym and simulated in pybullet. In par
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code
In generative deep geometry learning, we often get many obj files remain to be rendered
a python prompt cli script for blender batch render In deep generative geometry learning, we always get many .obj files to be rendered. Our rendered i
Quickly visualize docker networks with graphviz.
Docker Network Graph Visualize the relationship between Docker networks and containers as a neat graphviz graph. Example Usage usage: docker-net-graph
Text Classification in Turkish Texts with Bert
You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification
A foreign language learning aid using a neural network to predict probability of translating foreign words
Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is
Formulae is a Python library that implements Wilkinson's formulas for mixed-effects models.
formulae formulae is a Python library that implements Wilkinson's formulas for mixed-effects models. The main difference with other implementations li
The projects lets you extract glossary words and their definitions from a given piece of text automatically using NLP techniques
Unsupervised technique to Glossary and Definition Extraction Code Files GPT2-DefinitionModel.ipynb - GPT-2 model for definition generation. Data_Gener
Predict an emoji that is associated with a text
Sentiment Analysis Sentiment analysis in computational linguistics is a general term for techniques that quantify sentiment or mood in a text. Can you
🔎 Like Chardet. 🚀 Package for encoding & language detection. Charset detection.
Charset Detection, for Everyone 👋 The Real First Universal Charset Detector A library that helps you read text from an unknown charset encoding. Moti
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670
Convert onnx models to pytorch.
onnx2torch onnx2torch is an ONNX to PyTorch converter. Our converter: Is easy to use – Convert the ONNX model with the function call convert; Is easy
Telegram chatbot created with deep learning model (LSTM) and telebot library.
Telegram chatbot Telegram chatbot created with deep learning model (LSTM) and telebot library. Description This program will allow you to create very
TRACER: Extreme Attention Guided Salient Object Tracing Network implementation in PyTorch
TRACER: Extreme Attention Guided Salient Object Tracing Network This paper was accepted at AAAI 2022 SA poster session. Datasets All datasets are avai
A PaddlePaddle version of Neural Renderer, refer to its PyTorch version
Neural 3D Mesh Renderer in PadddlePaddle A PaddlePaddle version of Neural Renderer, refer to its PyTorch version Install Run: pip install neural-rende
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models This repo contains a barebones implementation for the atta
An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022
Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any
Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021
Introduction Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021 Prerequisites Python 3.8 and conda, get Conda CUDA 11
The python SDK for Eto, the AI focused data platform for teams bringing AI models to production
Eto Labs Python SDK This is the python SDK for Eto, the AI focused data platform for teams bringing AI models to production. The python SDK makes it e
Joint learning of images and text via maximization of mutual information
mutual_info_img_txt Joint learning of images and text via maximization of mutual information. This repository incorporates the algorithms presented in
SPEAR: Semi suPErvised dAta progRamming
Semi-Supervised Data Programming for Data Efficient Machine Learning SPEAR is a library for data programming with semi-supervision. The package implem
Code for Temporally Abstract Partial Models
Code for Temporally Abstract Partial Models Accompanies the code for the experimental section of the paper: Temporally Abstract Partial Models, Khetar
Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
WECHSEL Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. arXiv: https://arx
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
Library to enable Bayesian active learning in your research or labeling work.
Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components
Experiments on continual learning from a stream of pretrained models.
Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection
Why, hello there! This is the supporting notebook for the research paper — Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomal
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.
Official code repository for Continual Learning In Environments With Polynomial Mixing Times
Official code for Continual Learning In Environments With Polynomial Mixing Times Continual Learning in Environments with Polynomial Mixing Times This