axeloh's Stars
ML4ITS/mtad-gat-pytorch
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
menome/kepler4Neo
Load data from a Neo4J database into a kepler.gl map
AROS-Vision-Group/Mono-VO
Monocular Visual Odometry (VO) for over- and underwater scenario
wQvaale/DRL-Peg-Solitaire
🤖🎮Deep Reinforcement Learning for Peg Solitaire
mariusmcl/music-style-transfer
Style transfer for music using a WaveNet- like autoencoder structure
KDD-OpenSource/DeepADoTS
Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
sintel-dev/Orion
A machine learning library for detecting anomalies in signals.
NetManAIOps/OmniAnomaly
KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
naganandy/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
uoip/monoVO-python
A simple monocular visual odometry project in Python
TrustAGI-Lab/Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
magicleap/SuperPointPretrainedNetwork
PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking (https://arxiv.org/abs/1712.07629)
ML4ITS/tdt99-2020
Repository for the theory module TDT99
henrhoi/image-classification
Image classification using extensive feature extraction with simple classifiers in addition to transfer learning using CNNs (CS200 at UC Berkeley)
fractor/nntailoring
Capacity Estimation and Measuring Tools for Neural Networks
henrhoi/PersonalTrainerApplication
We are 7 students at NTNU, which in spring 2018 completed a project in the subject TDT4140 - Software Engineering. The project was to create a three-tier client application written in Java and JavaFX, where data could be retrieved over a standard network protocol.