Constantin Weisser's repositories
120-Data-Science-Interview-Questions
Answers to 120 commonly asked data science interview questions.
learningml
This repository demonstrates how to make a project pip installable, write a Python module in C++ and use scikit-learn, keras and spearmint
LHCbPVFinding
Track reconstruction for the LHCb experiment at CERN: Finding the primary vertices for particle physics events in the VertexLocator (Velo) detector
adaptive_binning_chisquared_2sam
This repository contains a 2 sample chi squared test the uses adaptive binning using the approach of Roederer et al. (http://onlinelibrary.wiley.com/doi/10.1002/1097-0320(20010901)45:1%3C47::AID-CYTO1143%3E3.0.CO;2-A/epdf)
autoencoder_demonstration
Demonstrating the workings of an autoencoder. A dataframe of n independent and m dependent variables is constructed and the autoencoder performs well when the encoding dimension is n or larger.
BayesNetBucketElim
Solving Bayesian Network Inference with Bucket Elimination
data_exploration_game
Navigate through a high dimensional data set
DL_resources
A list of Deep Learning resources
Eta_to_Ap_Gamma_Search
LHCb search for eta decaying to a photon and a dark photon (A'), which itself decays into two muons
FunctionScaler
Given a discrete probability density function learn a function that turns samples from the pdf into samples from desired distribution.
inspect_ai
Inspect: A framework for large language model evaluations
LHCb_PID_Compression
A benchmark to the challenge of compressing an obscured dataset containing Particle Identification
minimal_glo
Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"
MinorToFatal
Minor to Fatal: Predicting Injury Severity in Traffic Data - Project for 15.071 at MIT
MITJuniorLab
Some Jupyter notebook examples for data analysis
n-beats
Pytorch/Keras implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.
RandomNumberGenerator_OS_X_app
This is a very easy example of how to create a visual OS X app using python tkinter and py2app.
SAELens
Training Sparse Autoencoders on Language Models
spearmint_wrapper
A wrapper around the spearmint gaussian process to optimise hyperparameters for skearn, xgboost and keras
Supply-Distribution_Chain_Dartboard
Supply/Distribution Chain Planning at Dartboard Corporation : Case study
UnbiasedML
Investigating how to train a classifier such that no peaking structure is induced in the spectrum of control variables
weissercn.github.io
Constantin Weisser's website