david-woelfle
Follow
Stars
BEMCom, the Building Energy Management Communication framework, is a tool for the rapid implementation of hardware abstraction layers, i.e. software that allows communication with diverse devices o…
Lightning ⚡️ fast forecasting with statistical and econometric models.
A toolkit providing easy and unified access to building control environments for reinforcement learning (RL).
PyTorch implementation of 'Concrete Dropout'
Marginal likelihood estimation for model selection in deep learning
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A data source plugin for loading JSON APIs into Grafana.
Build Container Images In Kubernetes
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Instrument your FastAPI with Prometheus metrics.
Bash completion support for conda
Model summary in PyTorch similar to `model.summary()` in Keras
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
This repository has been archived and development has been moved to BuildingMOTIF.
Grundlegende Funktionen zur Entwicklung von webbasierten User Interfaces zur Interaktion zwischen Menschen und einem Gebäudeenergiemanagementsystem
Eine Simulationsumgebung zur Evaluierung und Bechmarking von Algorithmen zur Gebäudeenergieoptimierung.
Master Thesis project
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Official reinforcement learning environment for demand response and load shaping