Bernhard J. Conzelmann's repositories
accelerated_io_tools
Prototype SciDB plugins for faster ingest and export of data.
awesome-causal-inference
A (concise) curated list of awesome Causal Inference resources.
Awesome-Causal-Inference-1
A curated list of awesome work on causal inference, particularly in machine learning.
awesome-causality
Resources related to causality
awesome-causality-algorithms
An index of algorithms for learning causality with data
blobcaster
Blobcaster: Using Azure Blob Storage to Host a Podcast
BOSS
Bayesian Optimisation for String Spaces
CausalDiscoveryToolbox
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
causality
Tools for causal analysis
causalml
Uplift modeling and causal inference with machine learning algorithms
dash
Analytical Web Apps for Python & R. No JavaScript Required.
docker-library
Collection of Dockerfiles
dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
graph_nets
Build Graph Nets in Tensorflow
knockknock
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
pgmpy
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
saliency
TensorFlow implementation for SmoothGrad, Grad-CAM, Guided backprop, Integrated Gradients and other saliency techniques
streisand
Streisand sets up a new server running your choice of WireGuard, OpenConnect, OpenSSH, OpenVPN, Shadowsocks, sslh, Stunnel, or a Tor bridge. It also generates custom instructions for all of these services. At the end of the run you are given an HTML file with instructions that can be shared with friends, family members, and fellow activists.
template
This is the repository for the distill web framework
tf-explain
Interpretability Methods for tf.keras models with Tensorflow 2.0
Transformer_Time_Series
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)
tsgan
Time-series Generative Adversarial Networks (fork from the ML-AIM research group on bitbucket))
TuringTutorials
Educational material and tutorials for the Turing language