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100-days-of-ml-code

100-Days-Of-ML-Code中文版

anomalydetection-keras

apollo-kernel

Collections of Apollo Kernels

awesome-trajectory-prediction

bark

Open-Source Framework for Development, Simulation and Benchmarking of Behavior Planning Algorithms for Autonomous Driving

bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

bayesianrlforautonomousdriving

carla-rl

Reinforcement Learning codebase for self-driving car in Carla

chainerrl

ChainerRL is a deep reinforcement learning library built on top of Chainer.

cvpr_dnri

Code accompanying "Dynamic Neural Relational Inference" from CVPR 2020

deep-learning-uncertainty

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.

deep-rl-torcs

Autonomous Navigation using Deep Reinforcement Learning

deep_mahalanobis_detector

Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".

deeprl-agents

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

dropoutuncertaintyexps

Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

error-detection

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

evidential-deep-learning

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

frenet_path_planning

无人车路径规划算法demo

grip

interaction-dataset

Interaction Dataset Python Scripts

interpret_challenge_regular_generalizability_track

lanegcn

[ECCV2020 Oral] Learning Lane Graph Representations for Motion Forecasting

lbebm

learngit

macad-gym

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

ml-multiple-futures-prediction

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

motionplanning

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

ngsim-trajectory-animation

Simple visualization of NGSIM I-80 dataset

odin

A simple and effective method for detecting out-of-distribution images in neural networks.