Python Deep-Learning-for-Text-Document-Classification Resources

Citation Intent Classification Table of Contents About the Project Built With Installation Usage Acknowledgments About The Project Citation Intent Cla

Transfer_Learning_Remote_Sensing Simulation R codes for data generation and visualizations are in the folder simulation. Experiment: California Housin

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

NCL (Neighborhood-enrighed Contrastive Learning) This is the official PyTorch implementation for the paper: Zihan Lin*, Changxin Tian*, Yupeng Hou* Wa

copy-only-text-like-files-from-folder-python copy only text-like files from the folder This project is for those who want to copy only source code or

OceanScript is an Esoteric language used to encode and decode text into a formulation of characters - where the final result looks like waves in the ocean.

Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

A Broad Study on the Transferability of Visual Representations with Contrastive Learning This repository contains code for the paper: A Broad Study on

Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation

[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup

Causal Influence Detection for Improving Efficiency in Reinforcement Learning This repository contains the code release for the paper "Causal Influenc

BROS (BERT Relying On Spatiality) is a pre-trained language model focusing on text and layout for better key information extraction from documents. Given the OCR results of the document image, which are text and bounding box pairs, it can perform various key information extraction tasks, such as extracting an ordered item list from receipts

evolvingrl Supplementary Data for Evolving Reinforcement Learning Algorithms This dataset contains 1000 loss graphs from two experiments: 500 unique g

CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans

Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe

PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.

JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c

Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up

DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (

SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers This repo contains our codes for the paper "No Parameters Left Behind: Sensitivity Gu

SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri

GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

hashily is a python module that performs a variety of text decoding and encoding functions. It also various functions for encrypting and decrypting text using various ciphers.

PICO is an algorithm for exploiting Reinforcement Learning (RL) on Multi-agent Path Finding tasks. It is developed by the Multi-Agent Artificial Intel

Learning Efficient Online 3D Bin Packing on Packing Configuration Trees This repository is being continuously updated, please stay tuned！ Any code con

Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features

File-based TF-IDF Calculates keywords in a document, using a word corpus. Why? Because I found myself with hundreds of plain text files, with no way t

py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne

HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro

Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.

PUTO: PDF to Booklet converter Split given PDF document into 4 page groups and convert them to booklet format. It creates a PDF like shown below: Fir

Contrastive Product Matching This repository contains the code and data download links to reproduce the experiments of the paper "Supervised Contrasti

Playwright nonoCAPTCHA An async Python library to automate solving ReCAPTCHA v2 by audio using Playwright. Disclaimer This project is for educational

Table of Contents The general idea How these scripts work? Loading data Needed modules and global variables Parsing the arrays in dataset Extracting a

Vision-Transformer-Multiprocess-DistributedDataParallel-Apex Introduction This project uses ViT to perform image classification tasks on DATA set CIFA

Task-Informed Meta-Learning This repository contains examples of Task-Informed Meta-Learning (paper). We consider two tasks: Crop Type Classification

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I

NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio

Data, code and pretrained models for the paper Deep Surface Reconstruction from Point Clouds with Visibility Information.

CLASSIX Fast and explainable clustering based on sorting CLASSIX is a fast and explainable clustering algorithm based on sorting. Here are a few highl

Machine Learning and NLP: Advances and Applications This repository hosts the course materials used for a 3-day seminar "Machine Learning and NLP: Adv

ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg

Peer Loss functions This repository is the (Multi-Class & Deep Learning) Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels wi

Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2. It is trained (finetuned) on a curated list of approximately 45K Python (~470MB) files gathered from the Github. Currently, it just works properly on Python but not bad at other languages (thanks to GPT-2's power).

Volumetric TSDF Fusion of RGB-D Images in Python This is a lightweight python script that fuses multiple registered color and depth images into a proj

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

Pytorch implementation for A Novel Plug-in Module for Fine-Grained Visual Classification. fine-grained visual classification task.

pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.

ModelNet-C Code for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions". For the latest updates, see: sites.google.com

Fake News Detection Overview The proliferation of disinformation across social media has led the application of deep learning techniques to detect fak

A Graph Learning library for Humans These novel algorithms include but are not limited to: A graph construction and graph searching class can be found

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Authors: Tao Yu* Yichi Zhang* Zhiru Zhang Christopher De Sa *: Equal Contri

HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv

SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

AD Datasets Complete* and curated list of autonomous driving related datasets Contributing Contributions are very welcome! To add or update a dataset:

Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai

FedGS: Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT Preparation For instructions on generating data, plea

L3Cube-MahaCorpus L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

Towards Representation Learning for Atmospheric Dynamics (AtmoDist) The prediction of future climate scenarios under anthropogenic forcing is critical

Nash-MTL Official implementation of "Multi-Task Learning as a Bargaining Game". Setup environment conda create -n nashmtl python=3.9.7 conda activate

Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari

Efficient Deep Learning Systems This repository contains materials for the Efficient Deep Learning Systems course taught at the Faculty of Computer Sc

Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties 8.11.2021 Andrij Vasylenko I

CausIL A repo for Causal Imitation Learning under Temporally Correlated Noise. Running Experiments To re-train an expert, run: python experts/train_ex

CodeContests CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of pro

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

Learning-based Camera Calibration A Learning-based Camera Calibration Toolbox Paper The pdf file can be found here. @misc{zhang2022learningbased,

FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

Evolve plastic networks to be able to automatically acquire novel cognitive (meta-learning) tasks

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases

Hoax-Detector Authenticity of news has now become a major problem. The Idea is to classify the News into Real/Fake using Features from the Text Conten

py-self-organizing-map Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies. A SOM is a simple unsuperv

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py

TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo

DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.

This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain

Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.

An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th

TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake

APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod

scdlpicker SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP Objective This is a simple deep learning (DL) repicker module

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

AndroidApp_TextAnalysis Hi, there! This is code archive for Text Analysis and Topic Extraction from user_reviews of Android App. Dataset Source : http

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

This python library predicts the punctuation of English, Italian, French and German texts. We developed it to restore the punctuation of transcribed spoken language.

To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.