5023 Repositories
Python Dimension-Reduced-Turbulent-Flow-Data-From-Deep-Vector-Quantizers Libraries
CLIP (Contrastive Language–Image Pre-training) trained on Indonesian data
CLIP-Indonesian CLIP (Radford et al., 2021) is a multimodal model that can connect images and text by training a vision encoder and a text encoder joi
Python script to tabulate data formats like json, csv, html, etc
pyT PyT is a a command line tool and as well a library for visualising various data formats like: JSON HTML Table CSV XML, etc. Features Print table o
Grow Function: Generate 3D Stacked Bifurcating Double Deep Cellular Automata based organisms which differentiate using a Genetic Algorithm...
Grow Function: A 3D Stacked Bifurcating Double Deep Cellular Automata which differentiates using a Genetic Algorithm... TLDR;High Def Trees that you can mint as NFTs on Solana
Train neural network for semantic segmentation (deep lab V3) with pytorch in less then 50 lines of code
Train neural network for semantic segmentation (deep lab V3) with pytorch in 50 lines of code Train net semantic segmentation net using Trans10K datas
MS in Data Science capstone project. Studying attacks on autonomous vehicles.
Surveying Attack Models for CAVs Guide to Installing CARLA and Collecting Data Our project focuses on surveying attack models for Connveced Autonomous
Pipeline for training LSA models using Scikit-Learn.
Latent Semantic Analysis Pipeline for training LSA models using Scikit-Learn. Usage Instead of writing custom code for latent semantic analysis, you j
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
GDSC UIET KUK 📍 , welcomes you all to this amazing event where you will be introduced to the world of coding 💻 .
SentAugment is a data augmentation technique for semi-supervised learning in NLP.
SentAugment SentAugment is a data augmentation technique for semi-supervised learning in NLP. It uses state-of-the-art sentence embeddings to structur
A single model that parses Universal Dependencies across 75 languages.
A single model that parses Universal Dependencies across 75 languages. Given a sentence, jointly predicts part-of-speech tags, morphology tags, lemmas, and dependency trees.
Train Dense Passage Retriever (DPR) with a single GPU
Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G
Creating predictive checklists from data using integer programming.
Learning Optimal Predictive Checklists A Python package to learn simple predictive checklists from data subject to customizable constraints. For more
The official implementation of Relative Uncertainty Learning for Facial Expression Recognition
Relative Uncertainty Learning for Facial Expression Recognition The official implementation of the following paper at NeurIPS2021: Title: Relative Unc
Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]
Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi
A simple algorithm for extracting tree height in sparse scene from point cloud data.
TREE HEIGHT EXTRACTION IN SPARSE SCENES BASED ON UAV REMOTE SENSING This is the offical python implementation of the paper "Tree Height Extraction in
My notes on Data structure and Algos in golang implementation and python
My notes on DS and Algo Table of Contents Arrays LinkedList Trees Types of trees: Tree/Graph Traversal Algorithms Heap Priorty Queue Trie Graphs Graph
Minimal pure Python library for working with little-endian list representation of bit strings.
bitlist Minimal Python library for working with bit vectors natively. Purpose This library allows programmers to work with a native representation of
Google, Facebook, Amazon, Microsoft, Netflix tech interview questions
Algorithm and Data Structures Interview Questions HackerRank | Practice, Tutorials & Interview Preparation Solutions This repository consists of solut
Learn to code in any language. If
Learn to Code It is an intiiative undertaken by Student Ambassadors Club, Jamshoro for students who are absolute begineers in programming and want to
Multiple Imputation with Random Forests in Python
miceforest: Fast, Memory Efficient Imputation with lightgbm Fast, memory efficient Multiple Imputation by Chained Equations (MICE) with lightgbm. The
Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from time series data.
ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t
Very useful and necessary functions that simplify working with data
Additional-function-for-pandas Very useful and necessary functions that simplify working with data random_fill_nan(module_name, nan) - Replaces all sp
Deep Q Learning with OpenAI Gym and Pokemon Showdown
pokemon-deep-learning An openAI gym project for pokemon involving deep q learning. Made by myself, Sam Little, and Layton Webber. This code captures g
PLUR is a collection of source code datasets suitable for graph-based machine learning.
PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the datasets. This is done by offering a unified API and data structures for all datasets.
Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation
VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen
A tool to nowcast quarterly data with monthly indicators: US consumption example
MIDAS_Nowcaster A tool to nowcast quarterly data with monthly indicators: US consumption example Pulls data directly from FRED from a list of codes -
Data Exfiltration without ever making a connection. Using TCP header space.
TCPwned PoC toy code to exfiltrate data without ever making a TCP connection. This will never show up in firewall logs, much less, actually be monitor
Upgini : data search library for your machine learning pipelines
Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural
A Light CNN for Deep Face Representation with Noisy Labels
A Light CNN for Deep Face Representation with Noisy Labels Citation If you use our models, please cite the following paper: @article{wulight, title=
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
Inflated i3d network with inception backbone, weights transfered from tensorflow
I3D models transfered from Tensorflow to PyTorch This repo contains several scripts that allow to transfer the weights from the tensorflow implementat
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Open source annotation tool for machine learning practitioners.
doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ
Reproduce ResNet-v2(Identity Mappings in Deep Residual Networks) with MXNet
Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran
Tools for curating biomedical training data for large-scale language modeling
Tools for curating biomedical training data for large-scale language modeling
DISTIL: Deep dIverSified inTeractIve Learning.
DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.
EMNLP 2021 paper The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
The repository for the paper "When Do You Need Billions of Words of Pretraining Data?"
pretraining-learning-curves This is the repository for the paper When Do You Need Billions of Words of Pretraining Data? Edge Probing We use jiant1 fo
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
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat
Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks
Continuous Sparsification Implementation of Continuous Sparsification (CS), a method based on l_0 regularization to find sparse neural networks, propo
Multi-Task Deep Neural Networks for Natural Language Understanding
New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.
Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho
🥇Samsung AI Challenge 2021 1등 솔루션입니다🥇
MoT - Molecular Transformer Large-scale Pretraining for Molecular Property Prediction Samsung AI Challenge for Scientific Discovery This repository is
The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.
Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]
DANeS is an open-source E-newspaper dataset by collaboration between DATASET JSC (dataset.vn) and AIV Group (aivgroup.vn)
DANeS - Open-source E-newspaper dataset Source: Technology vector created by macrovector - www.freepik.com. DANeS is an open-source E-newspaper datase
TensorFlow (Python) implementation of DeepTCN model for multivariate time series forecasting.
DeepTCN TensorFlow TensorFlow (Python) implementation of multivariate time series forecasting model introduced in Chen, Y., Kang, Y., Chen, Y., & Wang
Deep learned, hardware-accelerated 3D object pose estimation
Isaac ROS Pose Estimation Overview This repository provides NVIDIA GPU-accelerated packages for 3D object pose estimation. Using a deep learned pose e
A production-ready, scalable Indexer for the Jina neural search framework, based on HNSW and PSQL
🌟 HNSW + PostgreSQL Indexer HNSWPostgreSQLIndexer Jina is a production-ready, scalable Indexer for the Jina neural search framework. It combines the
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types
A deep learning based semantic search platform that computes similarity scores between provided query and documents
semanticsearch This is a deep learning based semantic search platform that computes similarity scores between provided query and documents. Documents
Data preprocessing rosetta parser for python
datapreprocessing_rosetta_parser I've never done any NLP or text data processing before, so I wanted to use this hackathon as a learning opportunity,
Async boto3 with Autogenerated Data Classes
awspydk Async boto3 with Autogenerated JIT Data Classes Motivation This library is forked from an internal project that works with a lot of backend AW
Efficient training of deep recommenders on cloud.
HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and
A general framework for deep learning experiments under PyTorch based on pytorch-lightning
torchx Torchx is a general framework for deep learning experiments under PyTorch based on pytorch-lightning. TODO list gan-like training wrapper text
Implementation of Vaswani, Ashish, et al. "Attention is all you need."
Attention Is All You Need Paper Implementation This is my from-scratch implementation of the original transformer architecture from the following pape
Semi-automated vocabulary generation from semantic vector models
vec2word Semi-automated vocabulary generation from semantic vector models This script generates a list of potential conlang word forms along with asso
A command line tool that creates a super timeline from SentinelOne's Deep Visibility data
S1SuperTimeline A command line tool that creates a super timeline from SentinelOne's Deep Visibility data What does it do? The script accepts a S1QL q
Using deep learning to predict gene structures of the coding genes in DNA sequences of Arabidopsis thaliana
DeepGeneAnnotator: A tool to annotate the gene in the genome The master thesis of the "Using deep learning to predict gene structures of the coding ge
Visualize your pandas data with one-line code
PandasEcharts 简介 基于pandas和pyecharts的可视化工具 安装 pip 安装 $ pip install pandasecharts 源码安装 $ git clone https://github.com/gamersover/pandasecharts $ cd pand
A Pythonic framework for threat modeling
pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In
Open source person re-identification library in python
Open-ReID Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different da
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Official Repository for "Robust On-Policy Data Collection for Data Efficient Policy Evaluation" (NeurIPS 2021 Workshop on OfflineRL).
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation Source code of Robust On-Policy Data Collection for Data-Efficient Policy Evalua
Self-Supervised Image Denoising via Iterative Data Refinement
Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S
DeepAL: Deep Active Learning in Python
DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin
Data Consistency for Magnetic Resonance Imaging
Data Consistency for Magnetic Resonance Imaging Data Consistency (DC) is crucial for generalization in multi-modal MRI data and robustness in detectin
Automatic Data-Regularized Actor-Critic (Auto-DrAC)
Auto-DrAC: Automatic Data-Regularized Actor-Critic This is a PyTorch implementation of the methods proposed in Automatic Data Augmentation for General
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio
Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021
Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks
LMMNN Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks This is the working dire
Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting
QAConv Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting This PyTorch code is proposed in
Denoising Normalizing Flow
Denoising Normalizing Flow Christian Horvat and Jean-Pascal Pfister 2021 We combine Normalizing Flows (NFs) and Denoising Auto Encoder (DAE) by introd
This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"
BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro
Code for "On Memorization in Probabilistic Deep Generative Models"
On Memorization in Probabilistic Deep Generative Models This repository contains the code necessary to reproduce the experiments in On Memorization in
Toolbox to analyze temporal context invariance of deep neural networks
PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int
Deep Latent Force Models
Deep Latent Force Models This repository contains a PyTorch implementation of the deep latent force model (DLFM), presented in the paper, Compositiona
Representing Long-Range Context for Graph Neural Networks with Global Attention
Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N
Deep Markov Factor Analysis (NeurIPS2021)
Deep Markov Factor Analysis (DMFA) Codes and experiments for deep Markov factor analysis (DMFA) model accepted for publication at NeurIPS2021: A. Farn
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience This repository is the official implementation of [https://www.bi
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation
Configurations Change HOME_PATH in CONFIG.py as the current path Data Prepare CENSINCOME Download data Put census-income.data and census-income.test i
Auditing Black-Box Prediction Models for Data Minimization Compliance
Data-Minimization-Auditor An auditing tool for model-instability based data minimization that is introduced in "Auditing Black-Box Prediction Models f
Dataset and codebase for NeurIPS 2021 paper: Exploring Forensic Dental Identification with Deep Learning
Repository under construction. Example dataset, checkpoints, and training/testing scripts will be avaible soon! 💡 Collated best practices from most p
Code for models used in Bashiri et al., "A Flow-based latent state generative model of neural population responses to natural images".
A Flow-based latent state generative model of neural population responses to natural images Code for "A Flow-based latent state generative model of ne
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
LMPBT Supplementary code for the Paper entitled ``Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models"
[NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators"
G-PATE This is the official code base for our NeurIPS 2021 paper: "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of T
TAUFE: Task-Agnostic Undesirable Feature DeactivationUsing Out-of-Distribution Data
A deep neural network (DNN) has achieved great success in many machine learning tasks by virtue of its high expressive power. However, its prediction can be easily biased to undesirable features, which are not essential for solving the target task and are even imperceptible to a human, thereby resulting in poor generalization
Equivariant layers for RC-complement symmetry in DNA sequence data
Equi-RC Equivariant layers for RC-complement symmetry in DNA sequence data This is a repository that implements the layers as described in "Reverse-Co
A simple and useful implementation of LPIPS.
lpips-pytorch Description Developing perceptual distance metrics is a major topic in recent image processing problems. LPIPS[1] is a state-of-the-art
Hide sensitive information in images
Data-Preserved Script allowing to blur the most sensitive information on images. Prerequisites Before you begin, ensure you have met the following req
Official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021.
Introduction This repository is the official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021. Data-free Kno
A paper list of pre-trained language models (PLMs).
Large-scale pre-trained language models (PLMs) such as BERT and GPT have achieved great success and become a milestone in NLP.
A Python library for Deep Graph Networks
PyDGN Wiki Description This is a Python library to easily experiment with Deep Graph Networks (DGNs). It provides automatic management of data splitti
Sign data using symmetric-key algorithm encryption.
Sign data using symmetric-key algorithm encryption. Validate signed data and identify possible validation errors. Uses sha-(1, 224, 256, 385 and 512)/hmac for signature encryption. Custom hash algorithms are allowed. Useful shortcut functions for signing (and validating) dictionaries and URLs.
A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms
MatrixProfile MatrixProfile is a Python 3 library, brought to you by the Matrix Profile Foundation, for mining time series data. The Matrix Profile is
OpenL3: Open-source deep audio and image embeddings
OpenL3 OpenL3 is an open-source Python library for computing deep audio and image embeddings. Please refer to the documentation for detailed instructi
Minimalistic PyTorch training loop
Backbone for PyTorch training loop Will try to keep it minimalistic. pip install back from back import Bone Features Progress bar Checkpoints saving/l
Primitives for machine learning and data science.
An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt