244 Repositories
Python dynamic-pruning Libraries
TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction
TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction TSDF++ is a novel multi-object TSDF formulation that can encode mult
An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI, torch2trt to accelerate. our model support for int8, dynamic input and profiling. (Nvidia-Alibaba-TensoRT-hackathon2021)
Ultra_Fast_Lane_Detection_TensorRT An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI to accelerate. our model support for in
Block Sparse movement pruning
Movement Pruning: Adaptive Sparsity by Fine-Tuning Magnitude pruning is a widely used strategy for reducing model size in pure supervised learning; ho
:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)
R²SQL The PyTorch implementation of paper Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing. (AAAI 2021) Requirement
Neural Dynamic Policies for End-to-End Sensorimotor Learning
This is a PyTorch based implementation for our NeurIPS 2020 paper on Neural Dynamic Policies for end-to-end sensorimotor learning.
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).
DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical
This is the repository for CVPR2021 Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales
Intro This is the repository for CVPR2021 Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales Vehicle Sam
Dynamic Django settings.
Constance - Dynamic Django settings A Django app for storing dynamic settings in pluggable backends (Redis and Django model backend built in) with an
official code for dynamic convolution decomposition
Revisiting Dynamic Convolution via Matrix Decomposition (ICLR 2021) A pytorch implementation of DCD. If you use this code in your research please cons
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification》(AAAI 2021) GitHub:
LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)
RSCD (BS-RSCD & JCD) Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021) by Zhihang Zhong, Yinqiang Zheng, Imari Sato We co
Dynamic Slimmable Network (CVPR 2021, Oral)
Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int
Official implementation of "Dynamic Anchor Learning for Arbitrary-Oriented Object Detection" (AAAI2021).
DAL This project hosts the official implementation for our AAAI 2021 paper: Dynamic Anchor Learning for Arbitrary-Oriented Object Detection [arxiv] [c
A Python library for dynamic classifier and ensemble selection
DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Code accompanying "Dynamic Neural Relational Inference" from CVPR 2020
Code accompanying "Dynamic Neural Relational Inference" This codebase accompanies the paper "Dynamic Neural Relational Inference" from CVPR 2020. This
Makes dynamic linked shit "static". Amazing
static.py What does it do? You give it a dynamically linked binary and it will make a directory that has all the dependencies (recursively). It also f
A curated list of neural network pruning resources.
A curated list of neural network pruning and related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers and Awesome-NAS.
Oncall is a calendar tool designed for scheduling and managing on-call shifts. It can be used as source of dynamic ownership info for paging systems like http://iris.claims.
Oncall See admin docs for information on how to run and manage Oncall. Development setup Prerequisites Debian/Ubuntu - sudo apt-get install libsasl2-d
Dynamic DNS service
About nsupdate.info https://nsupdate.info is a free dynamic DNS service. nsupdate.info is also the name of the software used to implement it. If you l
Simple Dynamic Batching Inference
Simple Dynamic Batching Inference 解决了什么问题? 众所周知,Batch对于GPU上深度学习模型的运行效率影响很大。。。 是在Inference时。搜索、推荐等场景自带比较大的batch,问题不大。但更多场景面临的往往是稀碎的请求(比如图片服务里一次一张图)。 如果
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Master Docs License Apache MXNet (incubating) is a deep learning framework designed for both efficiency an
Deep learning with dynamic computation graphs in TensorFlow
TensorFlow Fold TensorFlow Fold is a library for creating TensorFlow models that consume structured data, where the structure of the computation graph
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 2021
Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 20
OPEM (Open Source PEM Fuel Cell Simulation Tool)
Table of contents What is PEM? Overview Installation Usage Executable Library Telegram Bot Try OPEM in Your Browser! MATLAB Issues & Bug Reports Contr
Dynamic image server for web and print
Quru Image Server - dynamic imaging for web and print QIS is a high performance web server for creating and delivering dynamic images. It is ideal for
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast
DyNet: The Dynamic Neural Network Toolkit
The Dynamic Neural Network Toolkit General Installation C++ Python Getting Started Citing Releases and Contributing General DyNet is a neural network
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m
Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks b
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast
pip-run - dynamic dependency loader for Python
pip-run provides on-demand temporary package installation for a single interpreter run. It replaces this series of commands (or their Windows equivale
Dynamic Django settings.
Constance - Dynamic Django settings A Django app for storing dynamic settings in pluggable backends (Redis and Django model backend built in) with an
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models
Learning to Simulate Dynamic Environments with GameGAN (CVPR 2020)
Learning to Simulate Dynamic Environments with GameGAN PyTorch code for GameGAN Learning to Simulate Dynamic Environments with GameGAN Seung Wook Kim,
:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)
R²SQL The PyTorch implementation of paper Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing. (AAAI 2021) Requirement
Colibri core is an NLP tool as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool ``colibri-patternmodeller`` whi ch allows you to build, view, manipulate and query pattern models.
Colibri Core by Maarten van Gompel, [email protected], Radboud University Nijmegen Licensed under GPLv3 (See http://www.gnu.org/licenses/gpl-3.0.html
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m
DO NOT USE. Implementation of Python 3.x for .NET Framework that is built on top of the Dynamic Language Runtime.
IronPython 3 IronPython3 is NOT ready for use yet. There is still much that needs to be done to support Python 3.x. We are working on it, albeit slowl
Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks b
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m