382 Repositories
Python sparse-modeling Libraries
Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral)
Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral) This is the official implementation of Focals Conv (CVPR 2022), a new sp
Implementation of CVPR'2022:Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors
Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors (CVPR 2022) Personal Web Pages | Paper | Project Page This repository contains
Constraint-based geometry sketcher for blender
Constraint-based sketcher addon for Blender that allows to create precise 2d shapes by defining a set of geometric constraints like tangent, distance,
My Solutions to 120 commonly asked data science interview questions.
Data_Science_Interview_Questions Introduction 👋 Here are the answers to 120 Data Science Interview Questions The above answer some is modified based
Curso práctico: NLP de cero a cien 🤗
Curso Práctico: NLP de cero a cien Comprende todos los conceptos y arquitecturas clave del estado del arte del NLP y aplícalos a casos prácticos utili
SparseInst: Sparse Instance Activation for Real-Time Instance Segmentation, CVPR 2022
SparseInst 🚀 A simple framework for real-time instance segmentation, CVPR 2022 by Tianheng Cheng, Xinggang Wang†, Shaoyu Chen, Wenqiang Zhang, Qian Z
The repository contains reproducible PyTorch source code of our paper Generative Modeling with Optimal Transport Maps, ICLR 2022.
Generative Modeling with Optimal Transport Maps The repository contains reproducible PyTorch source code of our paper Generative Modeling with Optimal
[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation
Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP
ConvMAE: Masked Convolution Meets Masked Autoencoders
ConvMAE ConvMAE: Masked Convolution Meets Masked Autoencoders Peng Gao1, Teli Ma1, Hongsheng Li2, Jifeng Dai3, Yu Qiao1, 1 Shanghai AI Laboratory, 2 M
KoBERTopic은 BERTopic을 한국어 데이터에 적용할 수 있도록 토크나이저와 BERT를 수정한 코드입니다.
KoBERTopic 모델 소개 KoBERTopic은 BERTopic을 한국어 데이터에 적용할 수 있도록 토크나이저와 BERT를 수정했습니다. 기존 BERTopic : https://github.com/MaartenGr/BERTopic/tree/05a6790b21009d
A quantum game modeling of pandemic (QHack 2022)
Contributors: @JongheumJung, @YoonjaeChung, @GyunghunKim Abstract In the regime of a global pandemic, leaders around the world need to consider variou
Large-scale language modeling tutorials with PyTorch
Large-scale language modeling tutorials with PyTorch 안녕하세요. 저는 TUNiB에서 머신러닝 엔지니어로 근무 중인 고현웅입니다. 이 자료는 대규모 언어모델 개발에 필요한 여러가지 기술들을 소개드리기 위해 마련하였으며 기본적으로
GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md
Official pytorch implementation for Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion (CVPR 2022)
Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion This repository contains a pytorch implementation of "Learning to Listen: Modeling
[ICCV2021] 3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds
3DVG-Transformer This repository is for the ICCV 2021 paper "3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds" Our method "3DV
Code for "Modeling Indirect Illumination for Inverse Rendering", CVPR 2022
Modeling Indirect Illumination for Inverse Rendering Project Page | Paper | Data Preparation Set up the python environment conda create -n invrender p
Official codebase for ICLR oral paper Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling
CLIORA This is the official codebase for ICLR oral paper: Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling. We introduce
SimCTG - A Contrastive Framework for Neural Text Generation
A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training
[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
Clean and readable code for Decision Transformer: Reinforcement Learning via Sequence Modeling
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ
Reading list for research topics in Masked Image Modeling
awesome-MIM Reading list for research topics in Masked Image Modeling(MIM). We list the most popular methods for MIM, if I missed something, please su
Rank-One Model Editing for Locating and Editing Factual Knowledge in GPT
Rank-One Model Editing (ROME) This repository provides an implementation of Rank-One Model Editing (ROME) on auto-regressive transformers (GPU-only).
Python package for concise, transparent, and accurate predictive modeling
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionaries
Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari
Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling
TGraM Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling, Qibin He, Xian Sun, Zhiyuan Yan, Beibei Li, Kun Fu Abstract Rece
A few of my adventures with Devito.
Devito-playbox A few of my adventures with Devito. This repository contains a few notebooks and scripts that will lead me in the road of learning this
Generative Flow Networks for Discrete Probabilistic Modeling
Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo
A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model
A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid symptoms or not by simply inputting certain values like oxygen level , breath rate , age, Vaccination done or not etc. with the help of kaggle database.
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S
TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce
NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models
NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients
Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner
Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges
OpenIPDM is a MATLAB open-source platform that stands for infrastructures probabilistic deterioration model
Open-Source Toolbox for Infrastructures Probabilistic Deterioration Modelling OpenIPDM is a MATLAB open-source platform that stands for infrastructure
A classification model capable of accurately predicting the price of secondhand cars
The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!
Title: Graduate-Admissions-Predictor
The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations have been created for understanding the data. 80% accuracy was achieved on the test set.
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network
Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers
Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f
DTCN IJCAI - Sequential prediction learning framework and algorithm
DTCN This is the implementation of our paper "Sequential Prediction of Social Me
BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions
BERTopic BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable
Contains modeling practice materials and homework for the Computational Neuroscience course at Okinawa Institute of Science and Technology
A310 Computational Neuroscience - Okinawa Institute of Science and Technology, 2022 This repository contains modeling practice materials and homework
Modeling and Simulation of Satellite Servicing Manipulators
Modeling and Simulation of Satellite Servicing Manipulators Final Project for the course ENPM662: Introduction to Robot Modeling (Fall 2021). This pro
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).
This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML)
package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre
Official implementation of Sparse Transformer-based Action Recognition
STAR Official implementation of S parse T ransformer-based A ction R ecognition Dataset download NTU RGB+D 60 action recognition of 2D/3D skeleton fro
Scaling Vision with Sparse Mixture of Experts
Scaling Vision with Sparse Mixture of Experts This repository contains the code for training and fine-tuning Sparse MoE models for vision (V-MoE) on I
Classification Modeling: Probability of Default
Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information
Classification Modeling: Probability of Default
Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection Implementation of the Uniform DL Representation for AD algorithm describ
Data-driven reduced order modeling for nonlinear dynamical systems
SSMLearn Data-driven Reduced Order Models for Nonlinear Dynamical Systems This package perform data-driven identification of reduced order model based
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
Bayesian Modeling and Computation in Python
Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in
A python tutorial on bayesian modeling techniques (PyMC3)
Bayesian Modelling in Python Welcome to "Bayesian Modelling in Python" - a tutorial for those interested in learning how to apply bayesian modelling t
Neural network pruning for finding a sparse computational model for controlling a biological motor task.
MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo
A vanilla 3D face modeling on pose-invariant and multi-lightning image data
3D-Face-Modeling A vanilla 3D face modeling on pose-invariant and multi-lightning image data Table of Contents Background Install Usage Contributing B
Predictive Modeling & Analytics on Home Equity Line of Credit
Predictive Modeling & Analytics on Home Equity Line of Credit Data (Python) HMEQ Data Set In this assignment we will use Python to examine a data set
Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.
Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the
Approaches to modeling terrain and maps in python
topography 🌎 Contains different approaches to modeling terrain and topographic-style maps in python Features Inverse Distance Weighting (IDW) A given
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Custom studies about block sparse attention.
Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention(块稀疏注意力)的研究总结(持续更新中)。按时间顺序,主要分为如下三部分: PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A
NLP techniques such as named entity recognition, sentiment analysis, topic modeling, text classification with Python to predict sentiment and rating of drug from user reviews.
This file contains the following documents sumbited for Baruch CIS9665 group 9 fall 2021. 1. Dataset: drug_reviews.csv 2. python codes for text classi
Modeling cumulative cases of Covid-19 in the US during the Covid 19 Delta wave using Bayesian methods.
Introduction The goal of this analysis is to find a model that fits the observed cumulative cases of COVID-19 in the US, starting in Mid-July 2021 and
Fast Learning of MNL Model From General Partial Rankings with Application to Network Formation Modeling
Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN
PyTorch implementation of DCT fast weight RNNs
DCT based fast weights This repository contains the official code for the paper: Training and Generating Neural Networks in Compressed Weight Space. T
Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles
Correlation-Study-Climate-Change-EV-Adoption Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles I
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetu
Dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Coursera Machine Learning - Python code
Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen
News-Articles-and-Essays - NLP (Topic Modeling and Clustering)
NLP T5 Project proposal Topic Modeling and Clustering of News-Articles-and-Essays Students: Nasser Alshehri Abdullah Bushnag Abdulrhman Alqurashi OVER
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh
Sparse-dense operators implementation for Paddle
Sparse-dense operators implementation for Paddle This module implements coo, csc and csr matrix formats and their inter-ops with dense matrices. Feel
General neural ODE and DAE modules for power system dynamic modeling.
Py_PSNODE General neural ODE and DAE modules for power system dynamic modeling. The PyTorch-based ODE solver is developed based on torchdiffeq. Sample
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
A Python package to create, run, and post-process MODFLOW-based models.
Version 3.3.5 — release candidate Introduction FloPy includes support for MODFLOW 6, MODFLOW-2005, MODFLOW-NWT, MODFLOW-USG, and MODFLOW-2000. Other s
PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI).
PyBERT PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI). It uses the Traits/UI package of t
[PNAS2021] The neural architecture of language: Integrative modeling converges on predictive processing
The neural architecture of language: Integrative modeling converges on predictive processing Code accompanying the paper The neural architecture of la
Historical battle simulation package for Python
Jomini v0.1.4 Jomini creates military simulations by using mathematical combat models. Designed to be helpful for game developers, students, history e
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling Demos | Blog Post | Colab Notebook | Paper | MIDI-DDSP is a hierarchical
PyDynamica is a freely available agent-based economy simulation
PyDynamica PyDynamica is a pure python implementation of Sociodynamica, a virtual environment to simulate a simple economy with minimal dependencies.
SIR model parameter estimation using a novel algorithm for differentiated uniformization.
TenSIR Parameter estimation on epidemic data under the SIR model using a novel algorithm for differentiated uniformization of Markov transition rate m
A bunch of codes for procedurally modeling and texturing futuristic cities.
Procedural Futuristic City This is our final project for CPSC 479. We created a procedural futuristic city complete with Worley noise procedural textu
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees
Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe
Integrated physics-based and ligand-based modeling.
ComBind ComBind integrates data-driven modeling and physics-based docking for improved binding pose prediction and binding affinity prediction. Given
A 3D sparse LBM solver implemented using Taichi
taichi_LBM3D Background Taichi_LBM3D is a 3D lattice Boltzmann solver with Multi-Relaxation-Time collision scheme and sparse storage structure impleme
A novel framework to automatically learn high-quality scanning of non-planar, complex anisotropic appearance.
appearance-scanner About This repository is an implementation of the neural network proposed in Free-form Scanning of Non-planar Appearance with Neura
Contains links to publicly available datasets for modeling health outcomes using speech and language.
speech-nlp-datasets Contains links to publicly available datasets for modeling various health outcomes using speech and language. Speech-based Corpora
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network
Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution
Open source code for the paper of Neural Sparse Voxel Fields.
Neural Sparse Voxel Fields (NSVF) Project Page | Video | Paper | Data Photo-realistic free-viewpoint rendering of real-world scenes using classical co
The code for paper "Learning Implicit Fields for Generative Shape Modeling".
implicit-decoder The tensorflow code for paper "Learning Implicit Fields for Generative Shape Modeling", Zhiqin Chen, Hao (Richard) Zhang. Project pag
Adversarial Learning for Modeling Human Motion
Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l
Continuously evaluated, functional, incremental, time-series forecasting
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
New Modeling The Background CodeBase
Modeling the Background for Incremental Learning in Semantic Segmentation This is the updated official PyTorch implementation of our work: "Modeling t
[AAAI 2021] EMLight: Lighting Estimation via Spherical Distribution Approximation and [ICCV 2021] Sparse Needlets for Lighting Estimation with Spherical Transport Loss
EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas
Code for "OctField: Hierarchical Implicit Functions for 3D Modeling (NeurIPS 2021)"
OctField(Jittor): Hierarchical Implicit Functions for 3D Modeling Introduction This repository is code release for OctField: Hierarchical Implicit Fun