quantshah
Deep Learning Researcher @embedl. PhD in quantum physics. GSoC '16 (student @dipy), '19, '20, '21 (mentor @qutip)
@embedl Chalmers, Riken @qutip @pyquantum @qgradGothenburg, Sweden
Pinned Repositories
causal-fermion-systems
Optimization of operators in the causal fermion system formalism
gd-qpt
Gradient-descent quantum process tomography by learning Kraus operators
neural-quantum-states
Numerically represent quantum states with Restricted Boltzmann Machines
qst-cgan
Quantum state tomography with conditional generative adversarial networks
qst-nn
Classification and reconstruction of optical quantum states with deep neural networks
quantum-implicit-differentiation
Implicit differentiation of variational quantum algorithms
qutip
QuTiP: Quantum Toolbox in Python
qutip-jax
JAX backend for QuTiP
supertaxi
Taxi dispatching with reinforcement learning
quantshah's Repositories
quantshah/qst-cgan
Quantum state tomography with conditional generative adversarial networks
quantshah/gd-qpt
Gradient-descent quantum process tomography by learning Kraus operators
quantshah/quantum-implicit-differentiation
Implicit differentiation of variational quantum algorithms
quantshah/causal-fermion-systems
Optimization of operators in the causal fermion system formalism
quantshah/hqq
Official implementation of Half-Quadratic Quantization (HQQ)
quantshah/qutip-jax
JAX backend for QuTiP
quantshah/chalmers-sc-device
A simulator for the Chalmers superconducting qubit device
quantshah/ConvNeXt
Code release for ConvNeXt model
quantshah/cv
Curriculum Vitae
quantshah/digen
Diverse and generative ML benchmarks
quantshah/dipy
Diffusion MR Imaging in Python
quantshah/discs
DISCS: The code base for the Benchmark for Discrete Sampling
quantshah/gausspy
GaussPy: Python tool for implementing Autonomous Gaussian Decomposition
quantshah/ising2d
Parallel Monte Carlo simulations of the 2d Ising model
quantshah/Let-The-Quantum-Creep-In
Code for the paper "Let the Quantum Creep In: Designing Quantum Neural Network Models by Gradually Swapping Out Classical Components"
quantshah/me
Simple presentation
quantshah/ml4qtech-collection
Machine Learning for quantum technologies
quantshah/mlx
MLX: An array framework for Apple silicon
quantshah/models
Models and examples built with TensorFlow
quantshah/netket
Machine learning algorithms for many-body quantum systems
quantshah/pennylane
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
quantshah/piqs
Permutational Invariance Quantum Solver for Lindblad open quantum system dynamics
quantshah/qgrad
A Python library to integrate automatic differentiation tools such as Jax with QuTiP and related quantum software packages.
quantshah/qml
Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.
quantshah/qml-benchmarks
Code to benchmark quantum machine learning models
quantshah/quantshah.github.io
Personal site
quantshah/qutip-qip
The QuTiP quantum information processing package
quantshah/qutip-tensorflow
TensorFlow linear-algebra backend for QuTiP
quantshah/snap
Robust preparation of Wigner-negative states with optimized SNAP-displacement sequences
quantshah/talks
Talks on quantum, code and machine learning