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learning2sync

learning_to_diversify

This is the official code repository for ICCV2021 'Learning to Diversify from Single Domain'.

learning_to_execute

Learning to Execute

learningsimplealgorithms

We present an approach for learning simple algorithms such as copying, multi-digit addition and single digit multiplication directly from examples. Our framework consists of a set of interfaces, accessed by a controller. Typical interfaces are 1-D tapes or 2-D grids that hold the input and output data. For the controller, we explore a range of neural network-based models which vary in their ability to abstract the underlying algorithm from training instances and generalize to test examples with many thousands of digits. The controller is trained using Q-learning with several enhancements and we show that the bottleneck is in the capabilities of the controller rather than in the search incurred by Q-learning.

learningtocompare-pytorch

Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning

learningtocompare_fsl

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

learningwithastrongadversary

learningwithoutforgetting

Repository for the Learning without Forgetting paper, ECCV 2016

learntopayattention

PyTorch implementation of ICLR 2018 paper Learn To Pay Attention

lectures

Oxford Deep NLP 2017 course

lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

leea

Limited-evaluation evolutionary algorithm for neural nets

leela-zero

Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper.

lggan

Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

libact

Pool-based active learning in Python

libfacedetection

An open source library for face detection in images. The face detection speed can reach 1500FPS.

libfm

Library for factorization machines

libneuroml

This package provides Python libNeuroML, for working with neuronal models specified in NeuroML

librarian_led_data_scientist_training

Collaborative Computational Development, or, How to Run an NCBI-Style Hackathon

libvips

A fast image processing library with low memory needs.

lidar-annotator

Lidar annotation tool using ray tracing and bounding boxes.

lidtk

Language Identification Toolkit

lie-transformer-pytorch

Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch

lifelines

Survival analysis in Python

light-field-video

Light field video applications (e.g. video refocusing, focus tracking, changing aperture and view)

light-weight-refinenet

Light-Weight RefineNet for Real-Time Semantic Segmentation

lightcnn

A pytorch implement of "A Light CNN for Deep Face Representation with Noisy Labels"

lightgbm

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

lightnet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

lightrnn-nips2016-tensorflow_code

The tensorflow implementation of NIPS2016 paper "LightRNN: Memory and Computation-Efficient Recurrent Neural Networks" (https://arxiv.org/abs/1610.09893)