5192 Repositories
Python swiftui-learning Libraries
Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure
Geometric Vector Perceptron Code to accompany Learning from Protein Structure with Geometric Vector Perceptrons by B Jing, S Eismann, P Suriana, RJL T
Official implementation of SynthTIGER (Synthetic Text Image GEneratoR) ICDAR 2021
🐯 SynthTIGER: Synthetic Text Image GEneratoR Official implementation of SynthTIGER | Paper | Datasets Moonbin Yim1, Yoonsik Kim1, Han-cheol Cho1, Sun
An application that maps an image of a LaTeX math equation to LaTeX code.
Convert images of LaTex math equations into LaTex code.
A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer".
An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr
🧠 A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation.', ECCV 2016
Deep CORAL A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation. B Sun, K Saenko, ECCV 2016' Deep CORAL can learn
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.
Rainbow: Combining Improvements in Deep Reinforcement Learning
Rainbow Rainbow: Combining Improvements in Deep Reinforcement Learning [1]. Results and pretrained models can be found in the releases. DQN [2] Double
Implementation detail for paper "Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet"
Multi-level-colonoscopy-malignant-tissue-detection-with-adversarial-CAC-UNet Implementation detail for our paper "Multi-level colonoscopy malignant ti
Implementation of the paper "Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning"
Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning This is the implementation of the paper "Self-Promoted Prototype Refinement
Xeasy-ml is a packaged machine learning framework.
xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use
Object-aware Contrastive Learning for Debiased Scene Representation
Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo
The code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention.
CrossFormer This repository is the code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention. Introduction Existin
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
Evidently helps analyze machine learning models during validation or production monitoring
Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
Active learning for text classification in Python
Active Learning allows you to efficiently label training data in a small-data scenario.
Pytorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.
Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme
This is the code repository for Interpretable Machine Learning with Python, published by Packt.
Interpretable Machine Learning with Python, published by Packt
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.
meProp: Sparsified Back Propagation for Accelerated Deep Learning
meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]
Continuum Learning with GEM: Gradient Episodic Memory
Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory
Image Deblurring using Generative Adversarial Networks
DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,
CondenseNet: Light weighted CNN for mobile devices
CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua
Image restoration with neural networks but without learning.
Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s
Deep Learning Head Pose Estimation using PyTorch.
Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio
SmoothGrad implementation in PyTorch
SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro
PyTorch implementation of the YOLO (You Only Look Once) v2
PyTorch implementation of the YOLO (You Only Look Once) v2 The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorc
PyTorch Implementation of Realtime Multi-Person Pose Estimation project.
PyTorch Realtime Multi-Person Pose Estimation This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here Realtime_Multi-P
Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics
Interaction-Network-Pytorch Pytorch Implementraion of Interaction Networks for Learning about Objects, Relations and Physics. Interaction Network is a
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning
Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup
Image reconstruction done with untrained neural networks.
PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)
Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture
Canonical Appearance Transformations
CAT-Net: Learning Canonical Appearance Transformations Code to accompany our paper "How to Train a CAT: Learning Canonical Appearance Transformations
Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"
Minimal PyTorch implementation of Generative Latent Optimization This is a reimplementation of the paper Piotr Bojanowski, Armand Joulin, David Lopez-
Pytorch Implementation for CVPR2018 Paper: Learning to Compare: Relation Network for Few-Shot Learning
LearningToCompare Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning Howto download mini-imagenet and make
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
PyTorch implementation of Trust Region Policy Optimization
PyTorch implementation of TRPO Try my implementation of PPO (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons.
This's an implementation of deepmind Visual Interaction Networks paper using pytorch
Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch
Prototypical Networks for Few shot Learning in PyTorch
Prototypical Networks for Few shot Learning in PyTorch Simple alternative Implementation of Prototypical Networks for Few Shot Learning (paper, code)
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
A PyTorch Implementation of Neural IMage Assessment
NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc
Style transfer, deep learning, feature transform
FastPhotoStyle License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons
Dilated RNNs in pytorch
PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi
NIMA: Neural IMage Assessment
PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from
Official Pytorch implementation of ICLR 2018 paper Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge.
Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
YARR is Yet Another Robotics and Reinforcement learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
Implementation of Multistream Transformers in Pytorch
Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi
NLPShala , the best IDE for all Natural language processing tasks.
The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.
A curated list of amazingly awesome Cybersecurity datasets
A curated list of amazingly awesome Cybersecurity datasets
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
Pandas Machine Learning and Quant Finance Library Collection
Pandas Machine Learning and Quant Finance Library Collection
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning
H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,
[ICCV'21] PlaneTR: Structure-Guided Transformers for 3D Plane Recovery
PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)
Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning
T2F: text to face generation using Deep Learning
⭐ [NEW] ⭐ T2F - 2.0 Teaser (coming soon ...) Please note that all the faces in the above samples are generated ones. The T2F 2.0 will be using MSG-GAN
Compute FID scores with PyTorch.
FID score for PyTorch This is a port of the official implementation of Fréchet Inception Distance to PyTorch. See https://github.com/bioinf-jku/TTUR f
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod
PyTorch implementation of PNASNet-5 on ImageNet
PNASNet.pytorch PyTorch implementation of PNASNet-5. Specifically, PyTorch code from this repository is adapted to completely match both my implemetat
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model
CobraML: Completely Customizable A python ML library designed to give the end user full control
CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.
MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).
Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxiang Wang, Han Zhao, Bo Li.
Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver
CS583: Deep Learning
CS583: Deep Learning
Code Release for Learning to Adapt to Evolving Domains
EAML Code release for "Learning to Adapt to Evolving Domains" (NeurIPS 2020) Prerequisites PyTorch = 0.4.0 (with suitable CUDA and CuDNN version) tor
Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)
NDQ: Learning Nearly Decomposable Value Functions with Communication Minimization Note This codebase accompanies paper Learning Nearly Decomposable Va
Official code for UnICORNN (ICML 2021)
UnICORNN (Undamped Independent Controlled Oscillatory RNN) [ICML 2021] This repository contains the implementation to reproduce the numerical experime
ICML 21 - Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC
Deep Two-View Structure-from-Motion Revisited
Deep Two-View Structure-from-Motion Revisited This repository provides the code for our CVPR 2021 paper Deep Two-View Structure-from-Motion Revisited.
The official PyTorch code for 'DER: Dynamically Expandable Representation for Class Incremental Learning' accepted by CVPR2021
DER.ClassIL.Pytorch This repo is the official implementation of DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR 2021)
Spatial Contrastive Learning for Few-Shot Classification (SCL)
This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image classification in order to learn more general purpose embeddings, and facilitate the test-time adaptation to novel visual categories.
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020)
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020) About The goal of our research problem is illustrated below: give
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models
Towards Understanding and Mitigating Social Biases in Language Models This repo contains code and data for evaluating and mitigating bias from generat
Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.
This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019). A PyTorch implementation.
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set —— PyTorch implementation This is an unofficial offici
Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch
Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c
A text augmentation tool for named entity recognition.
neraug This python library helps you with augmenting text data for named entity recognition. Augmentation Example Reference from An Analysis of Simple
NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation (ACL-IJCNLP 2021)
NeuralWOZ This code is official implementation of "NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation". Sungdong Kim, Mi
Python package for machine learning for healthcare using a OMOP common data model
This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.
NeuralCompression is a Python repository dedicated to research of neural networks that compress data
NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.
A simple python tool for explore your object detection dataset
A simple tool for explore your object detection dataset. The goal of this library is to provide simple and intuitive visualizations from your dataset and automatically find the best parameters for generating a specific grid of anchors that can fit you data characteristics
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
This is the official repository of my book "Deep Learning with PyTorch Step-by-Step". Here you will find one Jupyter notebook for every chapter in the book.
Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)
Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)
A PyTorch Implementation of "Neural Arithmetic Logic Units"
Neural Arithmetic Logic Units [WIP] This is a PyTorch implementation of Neural Arithmetic Logic Units by Andrew Trask, Felix Hill, Scott Reed, Jack Ra
Pytorch implementation of Learning with Opponent-Learning Awareness
Pytorch implementation of Learning with Opponent-Learning Awareness using DiCE
A pytorch reproduction of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.
A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch
Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights
Piggyback: https://arxiv.org/abs/1801.06519 Pretrained masks and backbones are available here: https://uofi.box.com/s/c5kixsvtrghu9yj51yb1oe853ltdfz4q
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"
Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc
YOLOv3 in PyTorch ONNX CoreML TFLite
This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices
Pytorch implementation of the DeepDream computer vision algorithm
deep-dream-in-pytorch Pytorch (https://github.com/pytorch/pytorch) implementation of the deep dream (https://en.wikipedia.org/wiki/DeepDream) computer
PyTorch implementations of algorithms for density estimation
pytorch-flows A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invert
A very short and easy implementation of Quantile Regression DQN
Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx