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  • 👋 Hi, I’m @kanhaiya-gupta
  • 👀 I’m interested in Machine Learning Technique in High Energy Physics
  • 🌱 I’m currently learning Single top qaurk associated production with Z boson
  • 💞️ I’m looking to collaborate on Machine Learning Technique in High Energy Physics, Phenomenology & Experiment
  • 📫 How to reach me ... Email: [email protected]

Kanhaiya Gupta's Projects

feynman-path-integral icon feynman-path-integral

Python code that performs that Feynman path integral for a specified potential. Demonstrated by approximating the average energy of the quantum harmonic oscillator for various temperatures.

flrw icon flrw

A numerical exploration of Friedmann-Lemaitre-Robertson-Walker Metrics

gp-unfold icon gp-unfold

Using Gaussian processes for data unfolding in high-energy physics.

gpt icon gpt

A Python toolkit for lattice field theory, quantum computing, and machine learning

gw150914 icon gw150914

:wavy_dash::earth_africa::wavy_dash: Analyse GW150914 (gravitational waves)

hep-ml-resources icon hep-ml-resources

Listing of useful learning resources for machine learning applications in high energy physics (HEPML)

hep_ml icon hep_ml

Machine Learning for High Energy Physics.

higgsml icon higgsml

Repository for post higgs-competition model submission

ilc-cbm icon ilc-cbm

Internal Linear Combination For Cosmic Microwave Background

iml2019 icon iml2019

Tutorials for the 3rd IML Workshop 2019 at CERN.

julia icon julia

The Julia Programming Language

jupyter_tutorial_sas icon jupyter_tutorial_sas

A programming tutorial for looking at SAS Data with Python. Part of the 'Better with Scattering' Workshop.

keras-gan icon keras-gan

Keras implementations of Generative Adversarial Networks.

klfitter icon klfitter

Repository hosting the KLFitter library – the Kinematic Likelihood Fitter.

madminer icon madminer

Machine learning–based inference toolkit for particle physics

meco7312 icon meco7312

MECO7312 Advanced Statistics and Probability

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