7047 Repositories
Python learning-with-limited-labeled-data Libraries
Implementation and replication of ProGen, Language Modeling for Protein Generation, in Jax
ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'
HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea
[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.
LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequ
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences [CVPR2021]
Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi
ShapeGlot: Learning Language for Shape Differentiation
ShapeGlot: Learning Language for Shape Differentiation Created by Panos Achlioptas, Judy Fan, Robert X.D. Hawkins, Noah D. Goodman, Leonidas J. Guibas
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning
LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow
This is the pytorch code for the paper Curious Representation Learning for Embodied Intelligence.
Curious Representation Learning for Embodied Intelligence This is the pytorch code for the paper Curious Representation Learning for Embodied Intellig
Official repository for the paper "Going Beyond Linear Transformers with Recurrent Fast Weight Programmers"
Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.
XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code
Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather than invoking the Python interpreter, Tuplex generates optimized LLVM bytecode for the given pipeline and input data set.
pure-predict: Machine learning prediction in pure Python
pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.
ACL'2021: Learning Dense Representations of Phrases at Scale
DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search
A Bot To Get Info Of Telegram messages , Media , Channel id Group ID etc.
Info-Bot A Bot To Get Info Of Telegram messages , Media , Channel id Group ID etc. Get Info Of Your And Messages , Channels , Groups ETC... How to mak
An advanced real time threat intelligence framework to identify threats and malicious web traffic on the basis of IP reputation and historical data.
ARTIF is a new advanced real time threat intelligence framework built that adds another abstraction layer on the top of MISP to identify threats and malicious web traffic on the basis of IP reputation and historical data. It also performs automatic enrichment and threat scoring by collecting, processing and correlating observables based on different factors.
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2
Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot
The source codes for ACL 2021 paper 'BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data'
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for
Official PyTorch Implementation of Embedding Transfer with Label Relaxation for Improved Metric Learning, CVPR 2021
Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label
Implementation of the GBST block from the Charformer paper, in Pytorch
Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
Falken provides developers with a service that allows them to train AI that can play their games
Falken provides developers with a service that allows them to train AI that can play their games. Unlike traditional RL frameworks that learn through rewards or batches of offline training, Falken is based on training AI via realtime, human interactions.
A python library to build Model Trees with Linear Models at the leaves.
A python library to build Model Trees with Linear Models at the leaves.
Deep Learning Models for Causal Inference
Extensive tutorials for learning how to build deep learning models for causal inference using selection on observables in Tensorflow 2.
A data preprocessing package for time series data. Design for machine learning and deep learning.
A data preprocessing package for time series data. Design for machine learning and deep learning.
This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).
Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D
This is the antenna performance plotted from tinyGS reception data.
tinyGS-antenna-map This is the antenna performance plotted from tinyGS reception data. See their repository. The code produces a plot that provides Az
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.
XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
What is nnDetection? Simultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of hi
Meerkat provides fast and flexible data structures for working with complex machine learning datasets.
Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.
A scanpy extension to analyse single-cell TCR and BCR data.
Scirpy: A Scanpy extension for analyzing single-cell immune-cell receptor sequencing data Scirpy is a scalable python-toolkit to analyse T cell recept
Learning To Have An Ear For Face Super-Resolution
Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on
Shared Attention for Multi-label Zero-shot Learning
Shared Attention for Multi-label Zero-shot Learning Overview This repository contains the implementation of Shared Attention for Multi-label Zero-shot
CLIP: Connecting Text and Image (Learning Transferable Visual Models From Natural Language Supervision)
CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
SEDE SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their natural language description
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”
RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L
Cross-Modal Contrastive Learning for Text-to-Image Generation
Cross-Modal Contrastive Learning for Text-to-Image Generation This repository hosts the open source JAX implementation of XMC-GAN. Setup instructions
AllenNLP integration for Shiba: Japanese CANINE model
Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).
Gamestonk Terminal is an awesome stock and crypto market terminal
Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch
LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.
30 Days Of Machine Learning Using Pytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
Lint game data metafiles against GTA5.xsd for Rockstar's game engine (RAGE)
rage-lint Lint RAGE (only GTA5 at the moment) meta/XML files for validity based off of the GTA5.xsd generated from game code. This script accepts a se
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA
Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch
Social Media Network Focuses On Data Security And Being Community Driven Web App
privalise Social Media Network Focuses On Data Security And Being Community Driven Web App The Main Idea: We`ve seen social media web apps that focuse
Joint Learning of 3D Shape Retrieval and Deformation, CVPR 2021
Joint Learning of 3D Shape Retrieval and Deformation Joint Learning of 3D Shape Retrieval and Deformation Mikaela Angelina Uy, Vladimir G. Kim, Minhyu
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)
This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my thesis if you're curious or if you're looking for info I haven't documented. Mostly I would recommend giving a quick look to the figures beyond the introduction.
Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks
PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:
Craxk is a SINGLE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reproduced by a single machine.
What is Craxk ? Craxk is a UNIQUE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reprod
Rayvens makes it possible for data scientists to access hundreds of data services within Ray with little effort.
Rayvens augments Ray with events. With Rayvens, Ray applications can subscribe to event streams, process and produce events. Rayvens leverages Apache
Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(2021) paper
Semantic Diversity Learning for Zero-Shot Multi-label Classification Paper Official PyTorch Implementation Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Bar
Orthogonal Over-Parameterized Training
The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.
DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predicate.
DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic
Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).
[PDF] | [Slides] The official implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021 Long talk) Installation Inst
BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity.
BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity. The player needs to walk along a bridge to reach a goal location. When the player walks off the bridge into the water, the current will move it randomly until it gets washed back on the shore. A good agent in this environment avoids this stochastic trap
This repo will contain code to reproduce and build upon understanding transfer learning
What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.
A python to scratch API connector. Can fetch data from the API and send it back in cloud variables.
Scratch2py Scratch2py or S2py is a easy to use, versatile tool to communicate with the Scratch API Based of scratchclient by Raihan142857 Installation
BRepNet: A topological message passing system for solid models
BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin
Migrate data from SQL to NoSQL easily
Migrate data from SQL to NoSQL easily Installation 💯 pip install sql2nosql --upgrade Dependencies 📢 For the package to work, it first needs "clients
Meta-learning for NLP
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks Code for training the meta-learning models and fine-tuning on downstr
MolRep: A Deep Representation Learning Library for Molecular Property Prediction
MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p
SmartSim Infrastructure Library.
Home Install Documentation Slack Invite Cray Labs SmartSim SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and Ten
[ICML 2021] Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data
Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised
DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort
DatasetGAN This is the official code and data release for: DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort Yuxuan Zhang*, Huan Li
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar
CausaLM: Causal Model Explanation Through Counterfactual Language Models
CausaLM: Causal Model Explanation Through Counterfactual Language Models Authors: Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart Abstract: Understan
PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Representation
How to Reproduce our Results This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Represen
Outlier Exposure with Confidence Control for Out-of-Distribution Detection
OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De
Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image
NonCuboidRoom Paper Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image Cheng Yang*, Jia Zheng*, Xili Dai, Rui Tang, Yi Ma, Xiao
Code for "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" @ICRA2021
CloudAAE This is an tensorflow implementation of "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" Files log:
Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation"
EgoNet Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation". This repo inclu
Model-based 3D Hand Reconstruction via Self-Supervised Learning, CVPR2021
S2HAND: Model-based 3D Hand Reconstruction via Self-Supervised Learning S2HAND presents a self-supervised 3D hand reconstruction network that can join
This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons
Adversarial poison generation and evaluation. This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data
This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas
Learning Neural Network Subspaces
Learning Neural Network Subspaces Welcome to the codebase for Learning Neural Network Subspaces by Mitchell Wortsman, Maxwell Horton, Carlos Guestrin,
Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"
SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition [ArXiv+Supplementary] [IEEE Xplore RA-L 2021] [ICRA 2021 YouTube Video]
The official implementation of the CVPR2021 paper: Decoupled Dynamic Filter Networks
Decoupled Dynamic Filter Networks This repo is the official implementation of CVPR2021 paper: "Decoupled Dynamic Filter Networks". Introduction DDF is
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
NoW Evaluation This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard e
Code and data for "TURL: Table Understanding through Representation Learning"
TURL This Repo contains code and data for "TURL: Table Understanding through Representation Learning". Environment and Setup Data Pretraining Finetuni
Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)
GraspNet Baseline Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020). [paper] [dataset] [API] [do
The AugNet Python module contains functions for the fast computation of image similarity.
AugNet AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation arxiv link In our work, we propose AugNet, a new deep le
Pretraining Representations For Data-Efficient Reinforcement Learning
Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch
Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research
Megaverse Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research. The efficient design of the engine enables ph
Code for "Primitive Representation Learning for Scene Text Recognition" (CVPR 2021)
Primitive Representation Learning Network (PREN) This repository contains the code for our paper accepted by CVPR 2021 Primitive Representation Learni
Code for "LASR: Learning Articulated Shape Reconstruction from a Monocular Video". CVPR 2021.
LASR Installation Build with conda conda env create -f lasr.yml conda activate lasr # install softras cd third_party/softras; python setup.py install;
Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows
DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.
JittorVis - Visual understanding of deep learning model.
JittorVis is a deep neural network computational graph visualization library based on Jittor.
The `rtdl` library + The official implementation of the paper
The `rtdl` library + The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"
Neighborhood Contrastive Learning for Novel Class Discovery
Neighborhood Contrastive Learning for Novel Class Discovery This repository contains the official implementation of our paper: Neighborhood Contrastiv
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
An intelligent, flexible grammar of machine learning.
An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz
Pytorch implementation of Supporting Clustering with Contrastive Learning, NAACL 2021
Supporting Clustering with Contrastive Learning SCCL (NAACL 2021) Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ram
An tiny CLI to load data from a JSON File during development.
JSON Server - An tiny CLI to load data from a JSON File during development.
flexible time-series processing & feature extraction
tsflex is a toolkit for flexible time-series processing & feature extraction, making few assumptions about input data. Useful links Documentation Exam
LifeSaver automatically, periodically saves USB flash drive data into the PC
LifeSaver automatically, periodically saves USB flash drive data into the PC. Theoriticaly it will work with any any connected drive ex - Hard Disk ,SSD ... But, can't handle Backing up multipatition drives. I can guess, but cannot be sure of, how it will react to multipartiton system.
Save data from Instagram takeout to a SQLite database
instagram-to-sqlite Save data from a Instagram takeout to a SQLite database. Mise En Place git clone https://github.com/gavindsouza/instagram-to-sqlit
Thermal Control of Laser Powder Bed Fusion using Deep Reinforcement Learning
This repository is the implementation of the paper "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", linked here. The project makes use of the Deep Reinforcement Library stable-baselines3 to derive a control policy that maximizes melt pool depth consistency.
Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models
Patch-Rotation(PatchRot) Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models Submitted to Neurips2021 To