onism

100-Days-Of-ML-Code

100 Days of ML Coding

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

Deep-Learning-for-Tracking-and-Detection

Collection of papers, datasets, code and other resources for object tracking and detection using deep learning

deepbayes-2018

Seminars DeepBayes Summer School 2018

Complex-YOLO

Complex-YOLO: Real-time 3D Object Detection on Point Clouds pytorch Darknet

TrackerComponentLibrary

This is a collection of Matlab functions that are useful in the development of target tracking algorithms.

pyvarinf

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

learning-to-reweight-examples

PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

importance-sampling

Code for experiments regarding importance sampling for training neural networks

3DOD_thesis

3D Object Detection for Autonomous Driving in PyTorch, trained on the KITTI dataset.

segnet

A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

maf

Masked Autoregressive Flow

Continuous-ConvOp

The Continuous Convolution Operator Tracker (C-COT).

MOTBeyondPixels

Monocular multi-object tracking using simple and complementary 3D and 2D cues (ICRA 2018)

l2hmc

TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network

Neural-Decision-Forests

An implementation of the Deep Neural Decision Forests in PyTorch

DeepTracking

Source code of DeepTracking research project

NAF

Experiments for the Neural Autoregressive Flows paper

snail

A PyTorch implementation of the blocks from the _A Simple Neural Attentive Meta-Learner_ paper

ciwt

This repository contains code for the tracking system as described in ''Combined Image- and World-Space Tracking in Traffic Scenes'', ICRA 2017.

pyfilter

Particle filtering and sequential parameter inference in Python

SIVI

Using neural networks to build an expressive hierarchical distribution; A variational inference method to accurately estimate the posterior uncertainty; A fast and general method for approximate Bayesian inference. (ICML 2018)

bssm

Bayesian Inference of State Space Models

snl

Sequential Neural Likelihood

kernel_hmc

Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"

masters_thesis

Real-time 3D Object Detection for Autonomous Driving

carstop

SAEM-ABC

example code for the paper by Picchini & Samson 2017, "Coupling stochastic EM and Approximate Bayesian Computation for parameter inference in state-space models", arXiv:1512.04831.

cost-optimal-particle-filter

We present demonstrative tools for exploring the themes described in Warrington and Dhir. "Generalising Cost-Optimal Particle Filtering." arXiv preprint arXiv:1805.00890 (2018).

dgp