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autonomous-robot-simulation

daemon

Disk monitor daemon for linux

deep-person-reid

Torchreid: Deep learning person re-identification in PyTorch.

deeprl-mountain-car

Deep Q learning model for solving Open AI Gym control task: Mountain car

detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

epfl-machine-learning-higgs-2019

Predicting the Higgs boson using regression models

flower

Render opening flower using Direct3D 11

gym

A toolkit for developing and comparing reinforcement learning algorithms.

image-analysis-and-pattern-recognition

Repository for Image analysis and pattern recognition labs

ll-1-analizator

Lexical and Syntax analizators for parsing expressions using LL(1) gramatik

marcov-chain-identification

Aim is to find properties (e.g. transition probabilities, stationary distribution, convergence rate) of Markov Chains by looking at their samples, and 2. Use these chains to sample from an arbitrary distribution - by using Metropolis Hasting algorithm.

ml_course

EPFL Machine Learning Course, Fall 2019

nlp_course

YSDA course in Natural Language Processing

noise2noise

An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"

object-tracking

Object tracking with centroid and kalman methods

passportapp

MRZ recognition application for Android

person_reid_baseline_pytorch

A tiny, friendly, strong pytorch implement of person re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial

planning_worlds_gazebo

Worlds to test planning algorithms in ROS/Gazebo

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-deeplab-xception

DeepLab v3+ model in PyTorch. Support different backbones.

pytorch-yolov3

Minimal PyTorch implementation of YOLOv3

solar

Optimal energy management for solar-powered cars

teb_local_planner

An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands (ROS Package)

vae_unicode

Experiments with Unicode characters visualization with VAE

weight-sharing-and-auxiliary-losses-for-classification

The objective of this project is to test different architectures to compare two digits visible in a two-channel image. It aims at showing in particular the impact of weight sharing, and of the use of an auxiliary loss to help the training of the main objective.