1331 Repositories
Python temporal-models Libraries
This repository is the official implementation of Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models Link to paper Abstract We study prediction of future out
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
PatrickStar: Parallel Training of Large Language Models via a Chunk-based Memory Management Meeting PatrickStar Pre-Trained Models (PTM) are becoming
Data, model training, and evaluation code for "PubTables-1M: Towards a universal dataset and metrics for training and evaluating table extraction models".
PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP. Democratize AI for everyone.
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earth’s Mantle Convection data set be built such that it can be readily run in
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
The source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation.
TME The source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation. Our implementation is based on TG
A PyTorch Lightning Callback for pushing models to the Hugging Face Hub 🤗⚡️
hf-hub-lightning A callback for pushing lightning models to the Hugging Face Hub. Note: I made this package for myself, mostly...if folks seem to be i
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
Anuvada: Interpretable Models for NLP using PyTorch
Anuvada: Interpretable Models for NLP using PyTorch So, you want to know why your classifier arrived at a particular decision or why your flashy new d
Quantized tflite models for ailia TFLite Runtime
ailia-models-tflite Quantized tflite models for ailia TFLite Runtime About ailia TFLite Runtime ailia TF Lite Runtime is a TensorFlow Lite compatible
Language Models for the legal domain in Spanish done @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish legal domain Language Model ⚖️ This repository contains the page for two main resources for the Spanish legal domain: A RoBERTa model: https:/
Hierarchical Few-Shot Generative Models
Hierarchical Few-Shot Generative Models Giorgio Giannone, Ole Winther This repo contains code and experiments for the paper Hierarchical Few-Shot Gene
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
Spatiotemporal resampling methods for mlr3
mlr3spatiotempcv Package website: release | dev Spatiotemporal resampling methods for mlr3. This package extends the mlr3 package framework with spati
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
This code provides various models combining dilated convolutions with residual networks
Overview This code provides various models combining dilated convolutions with residual networks. Our models can achieve better performance with less
PyTorch and Tensorflow functional model definitions
functional-zoo Model definitions and pretrained weights for PyTorch and Tensorflow PyTorch, unlike lua torch, has autograd in it's core, so using modu
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra
This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning (NeurIPS21).
Core-tuning This repository is the official implementation of ``Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regular
This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!
Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev
High-fidelity performance metrics for generative models in PyTorch
High-fidelity performance metrics for generative models in PyTorch
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
Collections of pydantic models
pydantic-collections The pydantic-collections package provides BaseCollectionModel class that allows you to manipulate collections of pydantic models
HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow
Class HiddenMarkovModel HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow 2.0 Installatio
This is an official source code for implementation on Extensive Deep Temporal Point Process
Extensive Deep Temporal Point Process This is an official source code for implementation on Extensive Deep Temporal Point Process, which is composed o
A collection of models for image-text generation in ACM MM 2021.
Bi-directional Image and Text Generation UMT-BITG (image & text generator) Unifying Multimodal Transformer for Bi-directional Image and Text Generatio
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual
FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.
BoMb-OT Python3 implementation of the papers On Transportation of Mini-batches: A Hierarchical Approach and Improving Mini-batch Optimal Transport via
Reverse engineer your pytorch vision models, in style
🔍 Rover Reverse engineer your CNNs, in style Rover will help you break down your CNN and visualize the features from within the model. No need to wri
A bunch of random PyTorch models using PyTorch's C++ frontend
PyTorch Deep Learning Models using the C++ frontend Gettting started Clone the repo 1. https://github.com/mrdvince/pytorchcpp 2. cd fashionmnist or
A Word Level Transformer layer based on PyTorch and 🤗 Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and 🤗 Transformers. How to use Install the library from PyPI: pip install transf
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
JittorVis - Visual understanding of deep learning models
JittorVis: Visual understanding of deep learning model JittorVis is an open-source library for understanding the inner workings of Jittor models by vi
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation A pytorch-version implementation codes of paper:
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
NLMpy - A Python package to create neutral landscape models
NLMpy is a Python package for the creation of neutral landscape models that are widely used by landscape ecologists to model ecological patterns
Learning to Prompt for Vision-Language Models.
CoOp Paper: Learning to Prompt for Vision-Language Models Authors: Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu CoOp (Context Optimization)
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
A collection of models for image - text generation in ACM MM 2021.
Bi-directional Image and Text Generation UMT-BITG (image & text generator) Unifying Multimodal Transformer for Bi-directional Image and Text Generatio
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
PyTorch implementation of D2C: Diffuison-Decoding Models for Few-shot Conditional Generation.
D2C: Diffuison-Decoding Models for Few-shot Conditional Generation Project | Paper PyTorch implementation of D2C: Diffuison-Decoding Models for Few-sh
Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.
CTC Decoding Algorithms Update 2021: installable Python package Python implementation of some common Connectionist Temporal Classification (CTC) decod
Rendering color and depth images for ShapeNet models.
Color & Depth Renderer for ShapeNet This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically bas
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.
简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布!新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理! 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言:面向事实一致性的生
Production First and Production Ready End-to-End Speech Recognition Toolkit
WeNet 中文版 Discussions | Docs | Papers | Runtime (x86) | Runtime (android) | Pretrained Models We share neural Net together. The main motivation of WeN
Mengzi Pretrained Models
中文 | English Mengzi 尽管预训练语言模型在 NLP 的各个领域里得到了广泛的应用,但是其高昂的时间和算力成本依然是一个亟需解决的问题。这要求我们在一定的算力约束下,研发出各项指标更优的模型。 我们的目标不是追求更大的模型规模,而是轻量级但更强大,同时对部署和工业落地更友好的模型。
Scalable training for dense retrieval models.
Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine
A framework to train language models to learn invariant representations.
Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)
PixelPyramids: Exact Inference Models from Lossless Image Pyramids This repository contains the PyTorch implementation of the paper PixelPyramids: Exa
Temporal Knowledge Graph Reasoning Triggered by Memories
MTDM Temporal Knowledge Graph Reasoning Triggered by Memories To alleviate the time dependence, we propose a memory-triggered decision-making (MTDM) n
Official implementation of "Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection" (ICCV Workshops 2021: RSL-CV).
Official PyTorch implementation of "Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection" This is the implementation of the paper "Syn
Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets).
TOQ-Nets-PyTorch-Release Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets). Temporal and Object Quantification Net
Discovering and Achieving Goals via World Models
Discovering and Achieving Goals via World Models [Project Website] [Benchmark Code] [Video (2min)] [Oral Talk (13min)] [Paper] Russell Mendonca*1, Ole
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
MIT-Machine Learning with Python–From Linear Models to Deep Learning
MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t
Temporal Meta-path Guided Explainable Recommendation (WSDM2021)
Temporal Meta-path Guided Explainable Recommendation (WSDM2021) TMER Code of paper "Temporal Meta-path Guided Explainable Recommendation". Requirement
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Introduction This is the repository of our accepted CIKM 2021 paper "Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Trans
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation Pytorch based implemention of Relational Temporal
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
Focal Frequency Loss - Official PyTorch Implementation This repository provides the official PyTorch implementation for the following paper: Focal Fre
CadQuery is an intuitive, easy-to-use Python module for building parametric 3D CAD models.
A python parametric CAD scripting framework based on OCCT
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.
PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
Hapi is a Python library for building Conceptual Distributed Model using HBV96 lumped model & Muskingum routing method
Current build status All platforms: Current release info Name Downloads Version Platforms Hapi - Hydrological library for Python Hapi is an open-sourc
The Multi-Mission Maximum Likelihood framework (3ML)
PyPi Conda The Multi-Mission Maximum Likelihood framework (3ML) A framework for multi-wavelength/multi-messenger analysis for astronomy/astrophysics.
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
Parrot Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more t
PyPI package for scaffolding out code for decision tree models that can learn to find relationships between the attributes of an object.
Decision Tree Writer This package allows you to train a binary classification decision tree on a list of labeled dictionaries or class instances, and
Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE)
OG-SPACE Introduction Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE) is a computational framewo
Analysis of rationale selection in neural rationale models
Neural Rationale Interpretability Analysis We analyze the neural rationale models proposed by Lei et al. (2016) and Bastings et al. (2019), as impleme
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
Graph Convolutional Networks for Temporal Action Localization (ICCV2019)
Graph Convolutional Networks for Temporal Action Localization This repo holds the codes and models for the PGCN framework presented on ICCV 2019 Graph
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees"
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees" Installa
Benchmarking the robustness of Spatial-Temporal Models
Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal
Codebase of deep learning models for inferring stability of mRNA molecules
Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen
The self-supervised goal reaching benchmark introduced in Discovering and Achieving Goals via World Models
Lexa-Benchmark Codebase for the self-supervised goal reaching benchmark introduced in 'Discovering and Achieving Goals via World Models'. Setup Create
Code & Data for the Paper "Time Masking for Temporal Language Models", WSDM 2022
Time Masking for Temporal Language Models This repository provides a reference implementation of the paper: Time Masking for Temporal Language Models
Neural text generators like the GPT models promise a general-purpose means of manipulating texts.
Boolean Prompting for Neural Text Generators Neural text generators like the GPT models promise a general-purpose means of manipulating texts. These m
Bayesian regularization for functional graphical models.
BayesFGM Paper: Jiajing Niu, Andrew Brown. Bayesian regularization for functional graphical models. Requirements R version 3.6.3 and up Python 3.6 and
New approach to benchmark VQA models
VQA Benchmarking This repository contains the web application & the python interface to evaluate VQA models. Documentation Please see the documentatio
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.
CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal
HyperCube: Implicit Field Representations of Voxelized 3D Models
HyperCube: Implicit Field Representations of Voxelized 3D Models Authors: Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysław Spurek [Pap