============================================================================================================ `MILA will stop developing Theano <https://groups.google.com/d/msg/theano-users/7Poq8BZutbY/rNCIfvAEAwAJ>`_. The PyMC developers are continuing Theano development in a `fork <https://github.com/pymc-devs/theano-pymc>`_. ============================================================================================================ To install the package, see this page: http://deeplearning.net/software/theano/install.html For the documentation, see the project website: http://deeplearning.net/software/theano/ Related Projects: https://github.com/Theano/Theano/wiki/Related-projects It is recommended that you look at the documentation on the website, as it will be more current than the documentation included with the package. In order to build the documentation yourself, you will need sphinx. Issue the following command: :: python ./doc/scripts/docgen.py Documentation is built into ``html/`` The PDF of the documentation can be found at ``html/theano.pdf`` ================ DIRECTORY LAYOUT ================ ``Theano`` (current directory) is the distribution directory. * ``Theano/theano`` contains the package * ``Theano/theano`` has several submodules: * ``gof`` + ``compile`` are the core * ``scalar`` depends upon core * ``tensor`` depends upon ``scalar`` * ``sparse`` depends upon ``tensor`` * ``sandbox`` can depend on everything else * ``Theano/examples`` are copies of the example found on the wiki * ``Theano/benchmark`` and ``Theano/examples`` are in the distribution, but not in the Python package * ``Theano/bin`` contains executable scripts that are copied to the bin folder when the Python package is installed * Tests are distributed and are part of the package, i.e. fall in the appropriate submodules * ``Theano/doc`` contains files and scripts used to generate the documentation * ``Theano/html`` is where the documentation will be generated
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.
Overview
Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"
Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy
256 Jan 05, 2023
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision (ICCV 2021)
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision (ICCV 2021) PyTorch implementation of Learning RAW-to-sRGB Mappings with Inaccurat
53 Dec 20, 2022
Publication describing 3 ML examples at NSLS-II and interfacing into Bluesky
Machine learning enabling high-throughput and remote operations at large-scale user facilities. Overview This repository contains the source code and
4 Sep 24, 2022
POT : Python Optimal Transport
POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa
1.7k Dec 31, 2022
code for Grapadora research paper experimentation
Road feature embedding selection method Code for research paper experimentation Abstract Traffic forecasting models rely on data that needs to be sens
0 May 26, 2022
Simple transformer model for CIFAR10
CIFAR-Transformer Simple transformer model for CIFAR10. Reference: https://www.tensorflow.org/text/tutorials/transformer https://github.com/huggingfac
9 Nov 07, 2022
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo
1 Dec 19, 2021
A unet implementation for Image semantic segmentation
Unet-pytorch a unet implementation for Image semantic segmentation 参考网上的Unet做分割的代码，做了一个针对kaggle地盐识别的，请去以下地址获取数据集: https://www.kaggle.com/c/tgs-salt-id
3 Jun 29, 2022
A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules
CapsNet-Tensorflow A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules Notes: The current version
3.8k Dec 29, 2022
An offline deep reinforcement learning library
d3rlpy: An offline deep reinforcement learning library d3rlpy is an offline deep reinforcement learning library for practitioners and researchers. imp
817 Jan 02, 2023
my graduation project is about live human face augmentation by projection mapping by using CNN
Live-human-face-expression-augmentation-by-projection my graduation project is about live human face augmentation by projection mapping by using CNN o
1 Mar 08, 2022
abess: Fast Best-Subset Selection in Python and R
abess: Fast Best-Subset Selection in Python and R Overview abess (Adaptive BEst Subset Selection) library aims to solve general best subset selection,
297 Dec 21, 2022
Official Pytorch implementation of "Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes", CVPR 2022
Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes / 3DCrowdNet News 💪 3DCrowdNet achieves the state-of-the-art accuracy on 3D
113 Dec 21, 2022
imbalanced-DL: Deep Imbalanced Learning in Python
imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc
19 Dec 28, 2022
KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite
KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite
80 Dec 27, 2022
NeRF Meta-Learning with PyTorch
NeRF Meta Learning With PyTorch nerf-meta is a PyTorch re-implementation of NeRF experiments from the paper "Learned Initializations for Optimizing Co
78 Dec 18, 2022
Multistream CNN for Robust Acoustic Modeling
Multistream Convolutional Neural Network (CNN) A multistream CNN is a novel neural network architecture for robust acoustic modeling in speech recogni
37 Sep 21, 2022
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions
Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act
1 Jun 09, 2022
TransVTSpotter: End-to-end Video Text Spotter with Transformer
TransVTSpotter: End-to-end Video Text Spotter with Transformer Introduction A Multilingual, Open World Video Text Dataset and End-to-end Video Text Sp
66 Dec 26, 2022
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This
159 Dec 28, 2022