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Name: Robin Karlsson
Type: User
Company: Nagoya University
Location: Tokyo, Japan
Name: Robin Karlsson
Type: User
Company: Nagoya University
Location: Tokyo, Japan
Computes the Alpha Precision and Recall metric for evaluating sample quality and diversity of generative models.
A collection of examples demonstrating the elegance and merits of representing model output and priors as probabilistic distributions, which can be integrated in a principled way using Bayes' theorem.
Conditional VAE experiment code in PyTorch Lightning
Repo for the Deep Learning Nanodegree Foundations program.
Simple DRNN (Deep Regression Neural Network) implementation in TensorFlow
Code to reproduce results in the paper "Learning to Predict Navigational Patterns from Partial Observations" (RA-L 2023)
A collection of filtering algorithms implemented as Jupyter notebooks
Google Maps Road BEV Generator
Collection of graph search algorithms and auxiliary functions
Latent variable BEV prediction model
OpenMMLab Detection Toolbox and Benchmark
OpenMMLab's next-generation platform for general 3D object detection.
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Native C++ interface for the OSQP solver
TRI-ML Monocular Depth Estimation Repository
Library for temporal accumulation of semantic point clouds generated from image and lidar senor data
Demonstration of applying direct and inverse perspective mapping to generate a top-down camera view
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
Code accompanying the paper "Predictive World Models from Real-World Partial Observations" (MOST 2023)
(ICLR) Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Image-to-Image Translation in PyTorch
PyTorch Tutorial for Deep Learning Researchers
Code to reproduce results in the paper 'Probabilistic Rainfall Estimation from Automotive Lidar'
A collection of reinforcement learning agents
Regularized Losses (rloss) for Weakly-supervised CNN Segmentation
Code to reproduce results in the paper "Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision" (ITSC 2021)
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
Library implementing the linear and logistic variational Bayes models as formulated in PRML and other sources
Variational inference for Gaussian mixture models
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.