5428 Repositories
Python scientific-machine-learning Libraries
(CVPR 2022) Energy-based Latent Aligner for Incremental Learning
Energy-based Latent Aligner for Incremental Learning Accepted to CVPR 2022 We illustrate an Incremental Learning model trained on a continuum of tasks
CVPR2022 paper "Dense Learning based Semi-Supervised Object Detection"
[CVPR2022] DSL: Dense Learning based Semi-Supervised Object Detection DSL is the first work on Anchor-Free detector for Semi-Supervised Object Detecti
[CVPR'22] Official PyTorch Implementation of Collaborative Transformers for Grounded Situation Recognition
[CVPR'22] Collaborative Transformers for Grounded Situation Recognition Paper | Model Checkpoint This is the official PyTorch implementation of Collab
Official Pytorch implementation of "Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes", CVPR 2022
Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes / 3DCrowdNet News 💪 3DCrowdNet achieves the state-of-the-art accuracy on 3D
Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capability)
Protein GLM (wip) Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capabil
PyTorch code for the paper "Complementarity is the King: Multi-modal and Multi-grained Hierarchical Semantic Enhancement Network for Cross-modal Retrieval".
Complementarity is the King: Multi-modal and Multi-grained Hierarchical Semantic Enhancement Network for Cross-modal Retrieval (M2HSE) PyTorch code fo
A port of muP to JAX/Haiku
MUP for Haiku This is a (very preliminary) port of Yang and Hu et al.'s μP repo to Haiku and JAX. It's not feature complete, and I'm very open to sugg
NAACL 2022: MCSE: Multimodal Contrastive Learning of Sentence Embeddings
MCSE: Multimodal Contrastive Learning of Sentence Embeddings This repository contains code and pre-trained models for our NAACL-2022 paper MCSE: Multi
Multi-objective gym environments for reinforcement learning.
MO-Gym: Multi-Objective Reinforcement Learning Environments Gym environments for multi-objective reinforcement learning (MORL). The environments follo
Official implementation of "Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation" (RSS 2022)
Intro Official implementation of "Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation" Robotics:Science and
Implementation of 🦩 Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch
🦩 Flamingo - Pytorch Implementation of Flamingo, state-of-the-art few-shot visual question answering attention net, in Pytorch. It will include the p
Direct application of DALLE-2 to video synthesis, using factored space-time Unet and Transformers
DALLE2 Video (wip) ** only to be built after DALLE2 image is done and replicated, and the importance of the prior network is validated ** Direct appli
Implementation of "Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis"
Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis Abstract: This work targets at using a general deep lea
Code for "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" paper
UNICORN 🦄 Webpage | Paper | BibTex PyTorch implementation of "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" pap
Implementation of the GVP-Transformer, which was used in the paper "Learning inverse folding from millions of predicted structures" for de novo protein design alongside Alphafold2
GVP Transformer (wip) Implementation of the GVP-Transformer, which was used in the paper Learning inverse folding from millions of predicted structure
Semi-automated OpenVINO benchmark_app with variable parameters
Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.
DeepGNN is a framework for training machine learning models on large scale graph data.
DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in
code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"
PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks) This repository contains the source code for the paper "A High-precis
Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch
MeMOT - Pytorch (wip) Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch. This paper is just one in a line of work, but importan
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
Smooth ReLU in PyTorch Unofficial PyTorch reimplementation of the Smooth ReLU (SmeLU) activation function proposed in the paper Real World Large Scale
A library to inspect itermediate layers of PyTorch models.
A library to inspect itermediate layers of PyTorch models. Why? It's often the case that we want to inspect intermediate layers of a model without mod
一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM,xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... (pytorch, tf2.0)
CTR Algorithm 根据论文, 博客, 知乎等方式学习一些CTR相关的算法 理解原理并自己动手来实现一遍 pytorch & tf2.0 保持一颗学徒的心! Schedule Model pytorch tensorflow2.0 paper LR ✔️ ✔️ \ FM ✔️ ✔️ Fac
Learning to compose soft prompts for compositional zero-shot learning.
Compositional Soft Prompting (CSP) Compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositional
A Flask Sentiment Analysis API, with visual implementation
The Sentiment Analysis Api was created using python flask module,it allows users to parse a text or sentence throught the (?text) arguement, then view the sentiment analysis of that sentence. It can be implementable into a web application.
Session-based Recommendation, CoHHN, price preferences, interest preferences, Heterogeneous Hypergraph, Co-guided Learning, SIGIR2022
This is our implementation for the paper: Price DOES Matter! Modeling Price and Interest Preferences in Session-based Recommendation Xiaokun Zhang, Bo
The repo for the paper "I3CL: Intra- and Inter-Instance Collaborative Learning for Arbitrary-shaped Scene Text Detection".
I3CL: Intra- and Inter-Instance Collaborative Learning for Arbitrary-shaped Scene Text Detection Updates | Introduction | Results | Usage | Citation |
Adansons Base is a data management tool that organizes metadata of unstructured data and creates and organizes datasets.
Adansons Base is a data management tool that organizes metadata of unstructured data and creates and organizes datasets. It makes dataset creation more effective and helps find essential insights from training results and improves AI performance.
Code for our SIGIR 2022 accepted paper : P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning
P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas
[arXiv22] Disentangled Representation Learning for Text-Video Retrieval
Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T
Official pytorch code for "APP: Anytime Progressive Pruning"
APP: Anytime Progressive Pruning Diganta Misra1,2,3, Bharat Runwal2,4, Tianlong Chen5, Zhangyang Wang5, Irina Rish1,3 1 Mila - Quebec AI Institute,2 L
Simulation environments for the CrazyFlie quadrotor: Used for Reinforcement Learning and Sim-to-Real Transfer
Phoenix-Drone-Simulation An OpenAI Gym environment based on PyBullet for learning to control the CrazyFlie quadrotor: Can be used for Reinforcement Le
Implementation of the Hybrid Perception Block and Dual-Pruned Self-Attention block from the ITTR paper for Image to Image Translation using Transformers
ITTR - Pytorch Implementation of the Hybrid Perception Block (HPB) and Dual-Pruned Self-Attention (DPSA) block from the ITTR paper for Image to Image
Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Retrieval.
Targeted Trojan-Horse Attacks on Language-based Image Retrieval Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Re
This is an open source library implementing hyperbox-based machine learning algorithms
hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed
Text classification is one of the popular tasks in NLP that allows a program to classify free-text documents based on pre-defined classes.
Deep-Learning-for-Text-Document-Classification Text classification is one of the popular tasks in NLP that allows a program to classify free-text docu
In this project we predict the forest cover type using the cartographic variables in the training/test datasets.
Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto
Athena is the only tool that you will ever need to optimize your portfolio.
Athena Portfolio optimization is the process of selecting the best portfolio (asset distribution), out of the set of all portfolios being considered,
Official repository of the paper Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors
SMDD-Synthetic-Face-Morphing-Attack-Detection-Development-dataset Official repository of the paper Privacy-friendly Synthetic Data for the Development
Bu repo SAHI uygulamasını mantığını öğreniyoruz.
SAHI-Learn: SAHI'den Beraber Kodlamak İster Misiniz Herkese merhabalar ben Kadir Nar. SAHI kütüphanesine gönüllü geliştiriciyim. Bu repo SAHI kütüphan
scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics.
scAR scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA
python debugger and anti-vm that checks if you're in a virtual machine or if someones trying to debug your file
Anti-Debug was made by Love ❌ code ✅ 🎉 ・What it checks for ・ Kills tools that can be used to debug your file ・ Exits if ran in vm (supports different
My implementation of Safaricom Machine Learning Codility test. The code has bugs, logical I guess I made errors and any correction will be appreciated.
Safaricom_Codility Machine Learning 2022 The test entails two questions. Question 1 was on Machine Learning. Question 2 was on SQL I ran out of time.
Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.
CNNs fruits360 Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class. CNN on a pretrained model Build a CNN on a pretrained model, Res
In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm was used to undersampling, SMOTEENN algorithm was applied as a combinatorial approach of over- and undersampling of credit card credit dataset from LendingClub. Machine learning models - BalancedRandomForestClassifier and EasyEnsembleClassifier were used to predict credit risk.
Overview of Credit Card Analysis In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm
A deep learning CNN model to identify and classify and check if a person is wearing a mask or not.
Face Mask Detection The Model is designed to check if any human is wearing a mask or not. Dataset Description The Dataset contains a total of 11,792 i
Implementaion of our ACL 2022 paper Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the
A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)
A variational Bayesian method for similarity learning in non-rigid image registration We provide the source code and the trained models used in the re
Repository for DNN training, theory to practice, part of the Large Scale Machine Learning class at Mines Paritech
DNN Training, from theory to practice This repository is complementary to the deep learning training lesson given to les Mines ParisTech on the 11th o
[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
This is the official implementation of our paper: Bowen Wen, Wenzhao Lian, Kostas Bekris, and Stefan Schaal. "CaTGrasp: Learning Category-Level Task-R
Codes for coreference-aware machine reading comprehension
Data and code for the paper "Tracing Origins: Coreference-aware Machine Reading Comprehension" at ACL2022. Dataset There are three folders for our thr
Code for ACL 2022 main conference paper "STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation".
STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"
MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved
An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and Machine Learning.
ALgorithmic_Trading_with_ML An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and
This is an official implementation of the CVPR2022 paper "Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots".
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"
On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl
API for RL algorithm design & testing of BCA (Building Control Agent) HVAC on EnergyPlus building energy simulator by wrapping their EMS Python API
RL - EmsPy (work In Progress...) The EmsPy Python package was made to facilitate Reinforcement Learning (RL) algorithm research for developing and tes
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
Memory Efficient Attention Pytorch Implementation of a memory efficient multi-head attention as proposed in the paper, Self-attention Does Not Need O(
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple
Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)
Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 (Spotlight) - Installation - Example - Citation This repository contains the
Comparison-of-OCR (KerasOCR, PyTesseract,EasyOCR)
Optical Character Recognition OCR (Optical Character Recognition) is a technology that enables the conversion of document types such as scanned paper
[CVPR 2022] Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement
Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement Announcement 🔥 We have not tested the code yet. We will fini
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).
Scaffold-Federated-Learning PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020). Environment numpy=
Codes for AAAI22 paper "Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum"
Paper For more details, please see our paper Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum which has been accepted a
Learning the Beauty in Songs: Neural Singing Voice Beautifier; ACL 2022 (Main conference); Official code
Learning the Beauty in Songs: Neural Singing Voice Beautifier Jinglin Liu, Chengxi Li, Yi Ren, Zhiying Zhu, Zhou Zhao Zhejiang University ACL 2022 Mai
Code for One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning (AAAI 2022)
One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning (AAAI 2022) Paper | Demo Requirements Python = 3.6 , Pytorch
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.
PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my
Neural-Machine-Translation - Implementation of revolutionary machine translation models
Neural Machine Translation Framework: PyTorch Repository contaning my implementa
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
ZEROGEN This repository contains the code for our paper “ZeroGen: Efficient Zero
ReLoss - Official implementation for paper "Relational Surrogate Loss Learning" ICLR 2022
Relational Surrogate Loss Learning (ReLoss) Official implementation for paper "R
DLWP: Deep Learning Weather Prediction
DLWP: Deep Learning Weather Prediction DLWP is a Python project containing data-
Autolfads-tf2 - A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS
autolfads-tf2 A TensorFlow 2.0 implementation of LFADS and AutoLFADS. Installati
Diabetes-Feature-Engineering - A machine learning model that can predict whether people have diabetes when their characteristics are specified
Diabetes-Feature-Engineering Aim Developing a machine learning model that can pr
SimCTG - A Contrastive Framework for Neural Text Generation
A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,
Job-Recommend-Competition - Vectorwise Interpretable Attentions for Multimodal Tabular Data
SiD - Simple Deep Model Vectorwise Interpretable Attentions for Multimodal Tabul
Kroomsa: A search engine for the curious
Kroomsa A search engine for the curious. It is a search algorithm designed to en
Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity
Product-based-recommendation-system A product based recommendation system which
Breaching - Breaching privacy in federated learning scenarios for vision and text
Breaching - A Framework for Attacks against Privacy in Federated Learning This P
Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser
Federated_Learning 💻 This projest include common test models for federated lear
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss
"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i
LotteryBuyPredictionWebApp - Lottery Purchase Prediction Model
Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization
Text-Summarization-using-NLP Text Summarization using NLP to fetch BBC News Arti
SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022
SafePicking Learning Safe Object Extraction via Object-Level Mapping Kentaro Wad
Python-samples - This project is to help someone need some practices when learning python language
Python-samples - This project is to help someone need some practices when learning python language
FAMIE is a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction (IE)
FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.
OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble
Wordle RL The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble I know there are more deterministic
Detecting drunk people through thermal images using Deep Learning (CNN)
Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab
Scientific Programming: A Crash Course
Scientific Programming: A Crash Course Welcome to the Scientific Programming course. My name is Jon Carr and I am a postdoc in Davide Crepaldi's lab.
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd
The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory
This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the
An ascii art generator that's actually good. Does edge detection and selects the most appropriate characters.
Ascii Artist An ascii art generator that's actually good. Does edge detection and selects the most appropriate characters. Installing Installing with
The visual framework is designed on the idea of module and implemented by mixin method
Visual Framework The visual framework is designed on the idea of module and implemented by mixin method. Its biggest feature is the mixins module whic
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM, XGBoost, Ranger...).
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Introduction OpenFed is a foundational library for federated learning
MVSDF - Learning Signed Distance Field for Multi-view Surface Reconstruction
MVSDF - Learning Signed Distance Field for Multi-view Surface Reconstruction This is the official implementation for the ICCV 2021 paper Learning Sign
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data"
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data" You can download the pretrained
GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery This is the code to the paper: Gradient-Based Learn
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning