941 Repositories
Python quantization-aware-training Libraries
Segmentation Training Pipeline
Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
First steps with Python in Life Sciences
First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
Repo for investigation of timeouts that happens with prolonged training on clients
Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o
GitHub Actions Docker training
GitHub-Actions-Docker-training Training exercise repository for GitHub Actions using a docker base. This repository should be cloned and used for trai
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s
X-VLM: Multi-Grained Vision Language Pre-Training
X-VLM: learning multi-grained vision language alignments Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts. Yan Zeng, Xi
ColossalAI-Examples - Examples of training models with hybrid parallelism using ColossalAI
ColossalAI-Examples This repository contains examples of training models with Co
A novel Engagement Detection with Multi-Task Training (ED-MTT) system
A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.
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
TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers.
TransMVSNet This repository contains the official implementation of the paper: "TransMVSNet: Global Context-aware Multi-view Stereo Network with Trans
A PyTorch implementation of VIOLET
VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV
ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur
[SDM 2022] Towards Similarity-Aware Time-Series Classification
SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition 2022)
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition
"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Pianote - An application that helps musicians practice piano ear training
Pianote Pianote is an application that helps musicians practice piano ear traini
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".
AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast
Official PyTorch implementation of Time-aware Large Kernel (TaLK) Convolutions (ICML 2020)
Time-aware Large Kernel (TaLK) Convolutions (Lioutas et al., 2020) This repository contains the source code, pre-trained models, as well as instructio
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta
This repo generates the training data and the model for Morpheus-Deblend
Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as
The code for our paper Semi-Supervised Learning with Multi-Head Co-Training
Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su
Explores the python bytecode, provides some tools to access it for fun and profit.
Pyasmtools - looking at the python bytecode for fun and profit. The pyasmtools library is made up of two parts A python bytecode disassembler . See Py
A Python module for the generation and training of an entry-level feedforward neural network.
ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
Implementation of Hire-MLP: Vision MLP via Hierarchical Rearrangement and An Image Patch is a Wave: Phase-Aware Vision MLP.
Hire-Wave-MLP.pytorch Implementation of Hire-MLP: Vision MLP via Hierarchical Rearrangement and An Image Patch is a Wave: Phase-Aware Vision MLP Resul
CVPR2021 Content-Aware GAN Compression
Content-Aware GAN Compression [ArXiv] Paper accepted to CVPR2021. @inproceedings{liu2021content, title = {Content-Aware GAN Compression}, auth
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
Depth-Aware Video Frame Interpolation (CVPR 2019)
DAIN (Depth-Aware Video Frame Interpolation) Project | Paper Wenbo Bao, Wei-Sheng Lai, Chao Ma, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang IEEE C
Discriminative Condition-Aware PLDA
DCA-PLDA This repository implements the Discriminative Condition-Aware Backend described in the paper: L. Ferrer, M. McLaren, and N. Brümmer, "A Speak
Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.
This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis
Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.
[SDM 2022] Towards Similarity-Aware Time-Series Classification
SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie
for a paper about leveraging discourse markers for training new models
TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis
Deep learning with TensorFlow and earth observation data.
Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu
[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting
[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting [Paper] [Project Website] [Google Colab] We propose a method for converting a
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
Syntax-aware Multi-spans Generation for Reading Comprehension (TASLP 2022)
SyntaxGen Syntax-aware Multi-spans Generation for Reading Comprehension (TASLP 2022) In this repo, we upload all the scripts for this work. Due to siz
Teaches a student network from the knowledge obtained via training of a larger teacher network
Distilling-the-knowledge-in-neural-network Teaches a student network from the knowledge obtained via training of a larger teacher network This is an i
This is the offline-training-pipeline for our project.
offline-training-pipeline This is the offline-training-pipeline for our project. We adopt the offline training and online prediction Machine Learning
Markdown Presentations for Tech Conferences, Training, Developer Advocates, and Educators.
March 1, 2021: Service on gitpitch.com has been shutdown permanently. GitPitch 4.0 Docs Twitter About Watch the Introducing GitPitch 4.0 Video Visit t
Jekyll is a simple, blog-aware, static site generator perfect for personal, project, or organization sites.
Jekyll Jekyll is a simple, blog-aware, static site generator perfect for personal, project, or organization sites. Think of it like a file-based CMS,
Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift (ICCV 2021)
Π-NAS This repository provides the evaluation code of our submitted paper: Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training
Learnable Boundary Guided Adversarial Training (ICCV2021)
Learnable Boundary Guided Adversarial Training This repository contains the implementation code for the ICCV2021 paper: Learnable Boundary Guided Adve
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)
FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl
Source code for Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active Learning - Official Pytorch implementation of the CVPR 2021 paper Kwanyoung Kim, Dongwon Park, Kwang In Kim,
Chinese version of GPT2 training code, using BERT tokenizer.
GPT2-Chinese Description Chinese version of GPT2 training code, using BERT tokenizer or BPE tokenizer. It is based on the extremely awesome repository
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset
AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin
Amazon SageMaker Delta Sharing Examples
This repository contains examples and related resources showing you how to preprocess, train, and serve your models using Amazon SageMaker with data fetched from Delta Lake.
The full training script for Enformer (Tensorflow Sonnet) on TPU clusters
Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt
Training DALL-E with volunteers from all over the Internet using hivemind and dalle-pytorch (NeurIPS 2021 demo)
Training DALL-E with volunteers from all over the Internet This repository is a part of the NeurIPS 2021 demonstration "Training Transformers Together
Crowd sourced training data for Rasa NLU models
NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free
Understanding and Overcoming the Challenges of Efficient Transformer Quantization
Transformer Quantization This repository contains the implementation and experiments for the paper presented in Yelysei Bondarenko1, Markus Nagel1, Ti
Implementations of LSTM: A Search Space Odyssey variants and their training results on the PTB dataset.
An LSTM Odyssey Code for training variants of "LSTM: A Search Space Odyssey" on Fomoro. Check out the blog post. Training Install TensorFlow. Clone th
VolumeGAN - 3D-aware Image Synthesis via Learning Structural and Textural Representations
VolumeGAN - 3D-aware Image Synthesis via Learning Structural and Textural Representations 3D-aware Image Synthesis via Learning Structural and Textura
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra
Official PyTorch implementation of the paper: DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample
DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape
PyTorch implementation of InstaGAN: Instance-aware Image-to-Image Translation
InstaGAN: Instance-aware Image-to-Image Translation Warning: This repo contains a model which has potential ethical concerns. Remark that the task of
[CVPR 2021] Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
Scan2Cap: Context-aware Dense Captioning in RGB-D Scans Introduction We introduce the task of dense captioning in 3D scans from commodity RGB-D sensor
[CVPR 2020] Transform and Tell: Entity-Aware News Image Captioning
Transform and Tell: Entity-Aware News Image Captioning This repository contains the code to reproduce the results in our CVPR 2020 paper Transform and
GoodNews Everyone! Context driven entity aware captioning for news images
This is the code for a CVPR 2019 paper, called GoodNews Everyone! Context driven entity aware captioning for news images. Enjoy! Model preview: Huge T
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.
Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S
TrainingBike - Code, models and schematics I've used to interface my stationary training bike with PC.
TrainingBike Code, models and schematics I've used to interface my stationary training bike with PC. You can find more information about the project i
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.
U-2-Net: U Square Net - Modified for paired image training of style transfer
U2-Net: U Square Net Modified for paired image training of style transfer This is an unofficial repo making use of the code which was made available b
StyleGAN2-ADA-training-jupyter - Training custom datasets in styleGAN2-ADA by NVIDIA using Jupyter
styleGAN2-ADA-training-jupyter Training custom datasets in styleGAN2-ADA on Jupyter Official StyleGAN2-ADA by NIVIDIA Paper Training Generative Advers
VQMIVC - Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion
VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion (Interspeech
CIFAR-10_train-test - training and testing codes for dataset CIFAR-10
CIFAR-10_train-test - training and testing codes for dataset CIFAR-10
Training Cifar-10 Classifier Using VGG16
opevcvdl-hw3 This project uses pytorch and Qt to achieve the requirements. Version Python 3.6 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.
Ppq - A powerful offline neural network quantization tool with custimized IR
PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A simple consistency training framework for semi-supervised image semantic segmentation
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT)
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi
implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"
MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
In this project, two programs can help you take full agvantage of time on the model training with a remote server
In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model training, like the model indices and unexpected interrupts. Then you can do something in time for your work.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking."
Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU
Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)
T-Zero This repository serves primarily as codebase and instructions for training, evaluation and inference of T0. T0 is the model developed in Multit
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H
Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.
SAFA: Structure Aware Face Animation (3DV2021) Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation. Getting Started
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program