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Erik Schultheis

S-Erik

Languages

Python56%Rust44%

Repos

15

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0

Forks

1

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Python

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Repositories

15
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S-Erik/OpenFermionFork

Python package for compiling and analyzing quantum algorithms to simulate electronic structures.

00Updated 1 week ago
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S-Erik/sunriseFork

Tequila Chemistry expansion package

Python00Updated 4 months ago
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S-Erik/tequilaFork

A High-Level Abstraction Framework for Quantum Algorithms

00Updated 1 month ago
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S-Erik/crackmnistFork

CrackMNIST - A Large-Scale Dataset for Crack Tip Detection in Digital Image Correlation Data

00Updated 1 year ago
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S-Erik/TenCirChem-NGFork

Quantum computational chemistry based on TensorCircuit

00Updated 11 months ago
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S-Erik/ffsimFork

Faster simulations of fermionic quantum circuits.

Python00Updated 11 months ago
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S-Erik/pennylaneFork

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

Python00Updated 12 months ago
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S-Erik/rustworkxFork

A high performance Python graph library implemented in Rust.

Rust00Updated 1 year ago
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S-Erik/dftworksFork

No description provided.

Rust00Updated 1 year ago
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S-Erik/qiskit-natureFork

Qiskit Nature is an open-source, quantum computing, framework for solving quantum mechanical natural science problems.

00Updated 1 year ago
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S-Erik/QDFTFork

Quantum Density Functional Theory: a quantum algorithm to solve the Kohn-Sham self-consistent equations.

00Updated 2 years ago
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S-Erik/raplFork

Rank Polymorphic array library for Rust.

Rust00Updated 2 years ago
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S-Erik/rustlings-solutionsFork

:crab: Small exercises to get you used to reading and writing Rust code!

Rust00Updated 2 years ago
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S-Erik/LeagueBuildsFork

Automatic League of Legends builds

Python00Updated 3 years ago
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S-Erik/visualkerasFork

Visualkeras is a Python package to help visualize Keras (either standalone or included in TensorFlow) neural network architectures. It allows easy styling to fit most needs. This module supports layered style architecture generation which is great for CNNs (Convolutional Neural Networks), and a graph style architecture, which works great for most models including plain feed-forward networks.

Python01Updated 1 year ago

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