Warning: This project does not have any current developer. See bellow.

Related tags

Deep Learningpylearn2
Overview

Pylearn2: A machine learning research library

Warning :

This project does not have any current developer. We will continue to review pull requests and merge them when appropriate, but do not expect new development unless someone decides to work on it.

There are other machine learning frameworks built on top of Theano that could interest you, such as: Blocks, Keras and Lasagne.

Pylearn2 is a library designed to make machine learning research easy.

Pylearn2 has online documentation. If you want to build a local copy of the documentation, run

python ./doc/scripts/docgen.py

More documentation is available in the form of commented examples scripts and ipython notebooks in the "pylearn2/scripts/tutorials" directory.

Pylearn2 was initially developed by David Warde-Farley, Pascal Lamblin, Ian Goodfellow and others during the winter 2011 offering of IFT6266, and is now developed by the LISA lab.

Quick start and basic design rules

  • Installation instructions are available here.
  • Subscribe to the pylearn-users Google group for important updates. Please write to this list for general inquiries and support questions.
  • Subscribe to the pylearn-dev Google group for important development updates. Please write to this list if you find any bug or want to contribute to the project.
  • Read through the documentation and examples mentioned above.
  • Pylearn2 should not force users to commit to the whole library. If someone just wants to implement a Model, they should be able to do that and not need to implement a TrainingAlgorithm. Try not to write library features that force users to buy into the whole library.
  • When writing reference implementations to go in the library, maximize code re-usability by decomposing your algorithm into a TrainingAlgorithm that trains a Model on a Dataset. It will probably do this by minimizing a Cost. In fact, you can probably use an existing TrainingAlgorithm.

Highlights

  • Pylearn2 was used to set the state of the art on MNIST, CIFAR-10, CIFAR-100, and SVHN. See pylearn2.models.maxout or pylearn2/scripts/papers/maxout
  • Pylearn2 provides a wrapper around Alex Krizhevsky's extremely efficient GPU convolutional network library. This wrapper lets you use Theano's symbolic differentiation and other capabilities with minimal overhead. See pylearn2.sandbox.cuda_convnet.

License and Citations

Pylearn2 is released under the 3-claused BSD license, so it may be used for commercial purposes. The license does not require anyone to cite Pylearn2, but if you use Pylearn2 in published research work we encourage you to cite this article:

Owner
Laboratoire d’Informatique des Systèmes Adaptatifs
Laboratoire d’Informatique des Systèmes Adaptatifs
The "breathing k-means" algorithm with datasets and example notebooks

The Breathing K-Means Algorithm (with examples) The Breathing K-Means is an approximation algorithm for the k-means problem that (on average) is bette

Bernd Fritzke 75 Nov 17, 2022
A PyTorch implementation of the continual learning experiments with deep neural networks

Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain

182 Dec 27, 2022
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

48 Dec 26, 2022
Image Segmentation Animation using Quadtree concepts.

QuadTree Image Segmentation Animation using QuadTree concepts. Usage usage: quad.py [-h] [-fps FPS] [-i ITERATIONS] [-ws WRITESTART] [-b] [-img] [-s S

Alex Eidt 29 Dec 25, 2022
mlpack: a scalable C++ machine learning library --

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

mlpack 4.2k Jan 09, 2023
MPViT:Multi-Path Vision Transformer for Dense Prediction

MPViT : Multi-Path Vision Transformer for Dense Prediction This repository inlcu

Youngwan Lee 272 Dec 20, 2022
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Thuy Ng 474 Dec 19, 2022
Newt - a Gaussian process library in JAX.

Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\

AaltoML 0 Nov 02, 2021
Code for our paper "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021

SimCLS Code for our paper: "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021 1. How to Install Requirements

Yixin Liu 150 Dec 12, 2022
Breast Cancer Classification Model is applied on a different dataset

Breast Cancer Classification Model is applied on a different dataset

1 Feb 04, 2022
Speckle-free Holography with Partially Coherent Light Sources and Camera-in-the-loop Calibration

Speckle-free Holography with Partially Coherent Light Sources and Camera-in-the-loop Calibration Project Page | Paper Yifan Peng*, Suyeon Choi*, Jongh

Stanford Computational Imaging Lab 19 Dec 11, 2022
This code is a near-infrared spectrum modeling method based on PCA and pls

Nirs-Pls-Corn This code is a near-infrared spectrum modeling method based on PCA and pls 近红外光谱分析技术属于交叉领域,需要化学、计算机科学、生物科学等多领域的合作。为此,在(北邮邮电大学杨辉华老师团队)指导下

Fu Pengyou 6 Dec 17, 2022
Multi-task yolov5 with detection and segmentation based on yolov5

YOLOv5DS Multi-task yolov5 with detection and segmentation based on yolov5(branch v6.0) decoupled head anchor free segmentation head README中文 Ablation

150 Dec 30, 2022
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
Arbitrary Distribution Modeling with Censorship in Real Time 59 2 60 3 Bidding Advertising for KDD'21

Arbitrary_Distribution_Modeling This repo implements the Neighborhood Likelihood Loss (NLL) and Arbitrary Distribution Modeling (ADM, with Interacting

7 Jan 03, 2023
Codebase for Time-series Generative Adversarial Networks (TimeGAN)

Codebase for Time-series Generative Adversarial Networks (TimeGAN)

Jinsung Yoon 532 Dec 31, 2022
An evaluation toolkit for voice conversion models.

Voice-conversion-evaluation An evaluation toolkit for voice conversion models. Sample test pair Generate the metadata for evaluating models. The direc

30 Aug 29, 2022
ATAC: Adversarially Trained Actor Critic

ATAC: Adversarially Trained Actor Critic Adversarially Trained Actor Critic for Offline Reinforcement Learning by Ching-An Cheng*, Tengyang Xie*, Nan

Microsoft 41 Dec 08, 2022
Deep learning (neural network) based remote photoplethysmography: how to extract pulse signal from video using deep learning tools

Deep-rPPG: Camera-based pulse estimation using deep learning tools Deep learning (neural network) based remote photoplethysmography: how to extract pu

Terbe Dániel 138 Dec 17, 2022
Automatic Image Background Subtraction

Automatic Image Background Subtraction This repo contains set of scripts for automatic one-shot image background subtraction task using the following

Oleg Sémery 6 Dec 05, 2022