Kanhaiya Gupta's Projects
Template for an ATLAS analysis repository.
The aim of ATLAS Open Data is help in physics analysis techniques used in experimental particle physics. The analysis performed here is just to learn and prepare myself for actual analysis project.
Exercises of the 7th Belle II Starter Kit Workshop based on the Online Textbook, release-05-01-16
How to do Bayesian statistical modelling using numpy and PyMC3
Hands-on boosted decision tree tutorial (using XGBoost) for September 2017 Fermilab Machine Learning Group Meeting.
Machine learning multiclassification task in particle physics experiment (Belle II) with deep neural networks (DNN) and gradient boosted decision trees (XGBoost).
Numerically computing correlation functions in 2d CFT, using Jupyter Notebooks.
Code for Anisotropies in the Microwave Background
Likelihood-free inference toolbox.
This is a research project on Charged Higgs Phenomenology.
Repository for the Charged Higgs analysis.
Machine learning analysis of CICY 3-folds
Treating the measurement of the same-sign W polarization fraction as a class imbalance problem
Public repository of the Cosmic Linear Anisotropy Solving System (master for the most recent version of the standard code; ExoCLASS branch for exotic energy injection; class_matter branch for FFTlog)
A tool box for cold-atom simulations.
Deep Learning with PyTorch, published by Packt
dEFT - differential Effective Field Theory
Analysis using reduced NanoAOD files created from CMS open data producing a high statistics di-muon spectrum
A mobile low-cost spectrometer for measuring radioactivity and the energy of ionising radiation like alpha particles and electrons
Design of Experiments analysis
DNNs, RNNs, Adversaries, CNNs and Other ML techniques
Research Proposal
Releases of EFTfitter
Carl implementation of Higgs EFT coupling parameters estimation using decomposed likelihood ratios.
Visualisation and analysis of electromagnetic fields.
Tutorials to accompany the statistics lectures at the European School of High-Energy Physics