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  • šŸ‘‹ Hi, Iā€™m @kanhaiya-gupta
  • šŸ‘€ Iā€™m interested in Machine Learning Technique in High Energy Physics
  • šŸŒ± Iā€™m currently learning Single top qaurk associated production with Z boson
  • šŸ’žļø Iā€™m looking to collaborate on Machine Learning Technique in High Energy Physics, Phenomenology & Experiment
  • šŸ“« How to reach me ... Email: [email protected]

Kanhaiya Gupta's Projects

minesfly icon minesfly

Modules to extend the functionality of ORS Dragonfly.

ml4phy-quantum-oscillators icon ml4phy-quantum-oscillators

Mini Project for the "Machine Learning for Physicists 2020" course. A RBM implementation of a set of quantum mechanical harmonic oscillators.

mlatgraddays icon mlatgraddays

Course of Machine Learning in Science and Industry at Heidelberg university

mlatimperial2017 icon mlatimperial2017

Materials for the course of machine learning at Imperial College organized by YSDA

mucalc icon mucalc

CMB distortion calculation for a WIMP annihilation

neurodiffeq icon neurodiffeq

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

nn2st icon nn2st

Two-Sample Test with Nearest Neighbors Density Ratio Estimation

omnifold icon omnifold

Universally unfolding collider data with machine learning-based reweighting.

pbdl-book icon pbdl-book

Welcome to the Physics-based Deep Learning Book (v0.1)

pdesbynns icon pdesbynns

This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means of neural networks using TensorFlow.

pinns icon pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

print3r icon print3r

Command line interface (CLI) for 3d printing

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