5192 Repositories
Python swiftui-learning Libraries
Tutorial on active learning with the Nvidia Transfer Learning Toolkit (TLT).
Active Learning with the Nvidia TLT Tutorial on active learning with the Nvidia Transfer Learning Toolkit (TLT). In this tutorial, we will show you ho
Code for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned Language Models in the wild .
🌳 Fingerprinting Fine-tuned Language Models in the wild This is the code and dataset for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned La
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cross-device use-cases over FEDn networks.
Public implementation of "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression" from CoRL'21
Self-Supervised Reward Regression (SSRR) Codebase for CoRL 2021 paper "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression "
PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"
Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati
Rubik's cube assistant on Flask webapp
webcube Rubik's cube assistant on Flask webapp. This webapp accepts the six faces of your cube and gives you the voice instructions as a response. Req
Deep learning-based approach to discovering Granger causality networks in multivariate time series
Granger causality discovery for neural networks.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"
Zero-shot-Fact-Verification-by-Claim-Generation This repository contains code and models for the paper: Zero-shot Fact Verification by Claim Generatio
Repository for the COLING 2020 paper "Explainable Automated Fact-Checking: A Survey."
Explainable Fact Checking: A Survey This repository and the accompanying webpage contain resources for the paper "Explainable Fact Checking: A Survey"
Disagreement-Regularized Imitation Learning
Due to a normalization bug the expert trajectories have lower performance than the rl_baseline_zoo reported experts. Please see the following link in
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.
Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition This is the research repository for Vid2
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M
This is the repo for Uncertainty Quantification 360 Toolkit.
UQ360 The Uncertainty Quantification 360 (UQ360) toolkit is an open-source Python package that provides a diverse set of algorithms to quantify uncert
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
HyperLib: Deep learning in the Hyperbolic space
HyperLib: Deep learning in the Hyperbolic space Background This library implements common Neural Network components in the hypberbolic space (using th
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
Exploring Visual Engagement Signals for Representation Learning
Exploring Visual Engagement Signals for Representation Learning Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie and Ser-Nam Lim C
Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning"
VANET Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning" Introduction This is the implementation of article VAN
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Implementation of ProteinBERT in Pytorch
ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc
Framework for joint representation learning, evaluation through multimodal registration and comparison with image translation based approaches
CoMIR: Contrastive Multimodal Image Representation for Registration Framework 🖼 Registration of images in different modalities with Deep Learning 🤖
Official code for "Mean Shift for Self-Supervised Learning"
MSF Official code for "Mean Shift for Self-Supervised Learning" Requirements Python = 3.7.6 PyTorch = 1.4 torchvision = 0.5.0 faiss-gpu = 1.6.1 In
Registration Loss Learning for Deep Probabilistic Point Set Registration
RLLReg This repository contains a Pytorch implementation of the point set registration method RLLReg. Details about the method can be found in the 3DV
chen2020iros: Learning an Overlap-based Observation Model for 3D LiDAR Localization.
Overlap-based 3D LiDAR Monte Carlo Localization This repo contains the code for our IROS2020 paper: Learning an Overlap-based Observation Model for 3D
Official code repository of the paper Learning Associative Inference Using Fast Weight Memory by Schlag et al.
Learning Associative Inference Using Fast Weight Memory This repository contains the offical code for the paper Learning Associative Inference Using F
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing This repository contains pytorch source code for AAAI2020 oral paper: Grapy-ML
Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)
This repo contains code for our paper State-only Imitation with Transition Dynamics Mismatch published at ICLR 2020. The code heavily uses the RL mach
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
AI and Machine Learning workflows on Anthos Bare Metal.
Hybrid and Sovereign AI on Anthos Bare Metal Table of Contents Overview Terraform as IaC Substrate ABM Cluster on GCE using Terraform TensorFlow ResNe
A PyTorch implementation of paper "Learning Shared Semantic Space for Speech-to-Text Translation", ACL (Findings) 2021
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant
AndroidEnv is a Python library that exposes an Android device as a Reinforcement Learning (RL) environment.
AndroidEnv is a Python library that exposes an Android device as a Reinforcement Learning (RL) environment.
A New, Interactive Approach to Learning Python
This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.
Implementation of ProteinBERT in Pytorch
ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc
A single Python file with some tools for visualizing machine learning in the terminal.
Machine Learning Visualization Tools A single Python file with some tools for visualizing machine learning in the terminal. This demo is composed of t
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning
AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning AutoPentest-DRL is an automated penetration testing framework based o
Official PyTorch implementation for "Mixed supervision for surface-defect detection: from weakly to fully supervised learning"
Mixed supervision for surface-defect detection: from weakly to fully supervised learning [Computers in Industry 2021] Official PyTorch implementation
FluxTraining.jl gives you an endlessly extensible training loop for deep learning
A flexible neural net training library inspired by fast.ai
DIRL: Domain-Invariant Representation Learning
DIRL: Domain-Invariant Representation Learning Domain-Invariant Representation Learning (DIRL) is a novel algorithm that semantically aligns both the
PyTorch implementation of SimSiam: Exploring Simple Siamese Representation Learning
SimSiam: Exploring Simple Siamese Representation Learning This is a PyTorch implementation of the SimSiam paper: @Article{chen2020simsiam, author =
The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.
DS3L This is the code for paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020. Setups The code is implem
Deep functional residue identification
DeepFRI Deep functional residue identification Citing @article {Gligorijevic2019, author = {Gligorijevic, Vladimir and Renfrew, P. Douglas and Koscio
Source code for "MusCaps: Generating Captions for Music Audio" (IJCNN 2021)
MusCaps: Generating Captions for Music Audio Ilaria Manco1 2, Emmanouil Benetos1, Elio Quinton2, Gyorgy Fazekas1 1 Queen Mary University of London, 2
Official codes for the paper "Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech"
ResDAVEnet-VQ Official PyTorch implementation of Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech What is in this repo? M
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.
Deep Learning Visuals contains 215 unique images divided in 23 categories
Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide".
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models and supports classification, regression and ranking. TF-DF is a TensorFlow wrapper around the Yggdrasil Decision Forests C++ libraries. Models trained with TF-DF are compatible with Yggdrasil Decision Forests' models, and vice versa.
True Few-Shot Learning with Language Models
This codebase supports using language models (LMs) for true few-shot learning: learning to perform a task using a limited number of examples from a single task distribution.
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.
Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex
PyTorch implementation of some learning rate schedulers for deep learning researcher.
pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu
AEC_DeepModel - Deep learning based acoustic echo cancellation baseline code
AEC_DeepModel - Deep learning based acoustic echo cancellation baseline code
Local Attention - Flax module for Jax
Local Attention - Flax Autoregressive Local Attention - Flax module for Jax Install $ pip install local-attention-flax Usage from jax import random fr
Code for our paper "Mask-Align: Self-Supervised Neural Word Alignment" in ACL 2021
Mask-Align: Self-Supervised Neural Word Alignment This is the implementation of our work Mask-Align: Self-Supervised Neural Word Alignment. @inproceed
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data
federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat
Orchest is a browser based IDE for Data Science.
Orchest is a browser based IDE for Data Science. It integrates your favorite Data Science tools out of the box, so you don’t have to. The application is easy to use and can run on your laptop as well as on a large scale cloud cluster.
Multitask Learning Strengthens Adversarial Robustness
Multitask Learning Strengthens Adversarial Robustness
Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification"
hypergraph_reid Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification" If you find this help your research,
Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
PAWS-TF 🐾 Implementation of Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples (PAWS)
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings This is the repository for t
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this
[CVPR'21 Oral] Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning [CVPR'21, Oral] By Zhicheng Huang*, Zhaoyang Zeng*, Yupan H
Implementation of Bidirectional Recurrent Independent Mechanisms (Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules)
BRIMs Bidirectional Recurrent Independent Mechanisms Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neura
Tensorflow implementation for Self-supervised Graph Learning for Recommendation
If the compilation is successful, the evaluator of cpp implementation will be called automatically. Otherwise, the evaluator of python implementation will be called.
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification
IAUnet This repository contains the code for the paper: IAUnet: Global Context-Aware Feature Learning for Person Re-Identification Ruibing Hou, Bingpe
A GPT, made only of MLPs, in Jax
MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat
Implementation of the paper "Shapley Explanation Networks"
Shapley Explanation Networks Implementation of the paper "Shapley Explanation Networks" at ICLR 2021. Note that this repo heavily uses the experimenta
(L2ID@CVPR2021) Boosting Co-teaching with Compression Regularization for Label Noise
Nested-Co-teaching (L2ID@CVPR2021) Pytorch implementation of paper "Boosting Co-teaching with Compression Regularization for Label Noise" [PDF] If our
Procedural 3D data generation pipeline for architecture
Synthetic Dataset Generator Authors: Stanislava Fedorova Alberto Tono Meher Shashwat Nigam Jiayao Zhang Amirhossein Ahmadnia Cecilia bolognesi Dominik
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li
Learning to Reconstruct 3D Manhattan Wireframes from a Single Image
Learning to Reconstruct 3D Manhattan Wireframes From a Single Image This repository contains the PyTorch implementation of the paper: Yichao Zhou, Hao
DataOps framework for Machine Learning projects.
Noronha DataOps Noronha is a Python framework designed to help you orchestrate and manage ML projects life-cycle. It hosts Machine Learning models ins
Paddle-Adversarial-Toolbox (PAT) is a Python library for Deep Learning Security based on PaddlePaddle.
Paddle-Adversarial-Toolbox Paddle-Adversarial-Toolbox (PAT) is a Python library for Deep Learning Security based on PaddlePaddle. Model Zoo Common FGS
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
An end-to-end machine learning library to directly optimize AUC loss
LibAUC An end-to-end machine learning library for AUC optimization. Why LibAUC? Deep AUC Maximization (DAM) is a paradigm for learning a deep neural n
An Unsupervised Graph-based Toolbox for Fraud Detection
An Unsupervised Graph-based Toolbox for Fraud Detection Introduction: UGFraud is an unsupervised graph-based fraud detection toolbox that integrates s
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"
When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi
GPT, but made only out of gMLPs
GPT - gMLP This repository will attempt to crack long context autoregressive language modeling (GPT) using variations of gMLPs. Specifically, it will
Expressive Power of Invariant and Equivaraint Graph Neural Networks (ICLR 2021)
Expressive Power of Invariant and Equivaraint Graph Neural Networks In this repository, we show how to use powerful GNN (2-FGNN) to solve a graph alig
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
Hybrid solving process for combinatorial optimization problems Combinatorial optimization has found applications in numerous fields, from aerospace to
Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way
Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.
A Lucid Framework for Transparent and Interpretable Machine Learning Models.
Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"
GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai
the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]
BGNet This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet] Environment Python 3.6.* C
Estimation of human density in a closed space using deep learning.
Siemens HOLLZOF challenge - Human Density Estimation Add project description here. Installing Dependencies: Install Python3 either system-wide, user-w
Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)
Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio
Deep learning (neural network) based remote photoplethysmography: how to extract pulse signal from video using deep learning tools
Deep-rPPG: Camera-based pulse estimation using deep learning tools Deep learning (neural network) based remote photoplethysmography: how to extract pu
Code for CVPR2021 paper "Learning Salient Boundary Feature for Anchor-free Temporal Action Localization"
AFSD: Learning Salient Boundary Feature for Anchor-free Temporal Action Localization This is an official implementation in PyTorch of AFSD. Our paper
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Keeping it safe - AI Based COVID-19 Tracker using Deep Learning and facial recognition
Keeping it safe - AI Based COVID-19 Tracker using Deep Learning and facial recognition
OpenVisionAPI server
🚀 Quick start An instance of ova-server is free and publicly available here: https://api.openvisionapi.com Checkout ova-client for a quick demo. Inst
Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.
Paddle-RLBooks Welcome to Paddle-RLBooks which is a reinforcement learning code study guide based on pure PaddlePaddle. 欢迎来到Paddle-RLBooks,该仓库主要是针对强化学
Graphsignal Logger
Graphsignal Logger Overview Graphsignal is an observability platform for monitoring and troubleshooting production machine learning applications. It h
Code for Learning Manifold Patch-Based Representations of Man-Made Shapes, in ICLR 2021.
LearningPatches | Webpage | Paper | Video Learning Manifold Patch-Based Representations of Man-Made Shapes Dmitriy Smirnov, Mikhail Bessmeltsev, Justi
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
CURL Rainbow Status: Archive (code is provided as-is, no updates expected) This is an implementation of CURL: Contrastive Unsupervised Representations
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
An All-MLP solution for Vision, from Google AI
MLP Mixer - Pytorch An All-MLP solution for Vision, from Google AI, in Pytorch. No convolutions nor attention needed! Yannic Kilcher video Install $ p
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai