AI · alternatives · 2026
24 alternatives to Quantum Evolution Kernel (FOSS quantum graph machine learning lib)
Hi HN, We're proud to announce the release of the Quantum Evolution Kernel! It's still an early version, so feedback is very much welcome. # What is it? Quantum evolution kernel is an open-source library designed for anyone interested in applying quantum computing to graph machine learning -- and you don’t even need a quantum computer in your living room to start using it! It has a wide range of graph machine learning applications, including prediction of molecular toxicity, as shown in the tutorial. # Why is it exciting? Quantum computing has huge potential, but it needs to be accessible…
Quantum Evolution Kernel is an open-source library that applies quantum computing to graph machine learning tasks without requiring physical quantum hardware. It supports applications like molecular toxicity prediction… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
filippo.io/mlkem768 is a pure-Go implementation of the post-quantum key exchange mechanism ML-KEM-768 optimized for correctness and readability.
2024 · words.filippo.io · its alternatives →
- 2
TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
- 3
Netmind Power▲272Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month
2023 · netmind.ai · its alternatives →
- 4MB
Beautiful Data Science
2020 · shahinrostami.com · its alternatives →
- 5
Accelerating open machine learning research with Cloud TPUs
2017 · sites.research.google · its alternatives →
- 6
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments. - AgnostiqHQ/covalent
2022 · github.com · its alternatives →
- 7
2016 · blog.otoro.net · its alternatives →
- 8AQ
2019 · qml.entropicalabs.io · its alternatives →
- 9
Simulate reverse causality using quantum suicide. Contribute to karldray/quantum development by creating an account on GitHub.
2016 · github.com · its alternatives →
- 10
Quip Network▲75Hey HN. I'm Colton (YC S21, ex-Acorns), one of the founders of Postquant Labs. My cofounder Richard is a cryptographer out of Draper Labs and DARPA. We're building Quip.Network, the first distributed quantum compute network. We just opened our testnet and wanted to share it here. The basic problem: quantum hardware is here and already competitive on certain optimization problems, but for most people, there's no way to access it. The machines cost millions and the hardware and research are gated by the companies who own them. Also, quantum providers regularly have machines sitting idle…
Apr 2026 · quip.network · its alternatives →
- 11
Optimal Quantile Approximation in Streams. Contribute to axiomhq/quantiles development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 12
A quantum chemisty library in jax. Contribute to lowdanie/hartree-fock-solver development by creating an account on GitHub.
Jan 2026 · github.com · its alternatives →
- 13
- 14
A graph-based functional API for building complex scikit-learn pipelines. - alegonz/baikal
2020 · github.com · its alternatives →
- 15QM
2020 · iris.entropicalabs.io · its alternatives →
- 16OS
Everyone saw the AlphaEvolve hype. I got obsessed with how it might work under the hood and decided to just build it myself. My setup uses GPT-4.1 to mutate matrix multiplication code, guided by a bunch of hand-crafted mutation strategies (loop reordering, tiling, Strassen, etc.). Each candidate is evaluated on both speed and accuracy. Then I apply Pareto selection with crowding distance to evolve better ones over generations. I ran into all the usual LLM reward hacks-returning the input, calling np.dot, etc. So I forced primitive-only implementations and tightly constrained the mutation…
2025 · its alternatives →
- 17HI
2013 · quantopian.com · its alternatives →
- 18RX
Hi all, long time lurker, first time poster. I want to share with you all something we've been working on for a while at Lambda: the Razer x Lambda Tensorbook: https://www.youtube.com/watch?v=wMh6Dhq7P_Q But before I tell you about it, I want to make this all about me, because I built this for me. See, while I'm genuinely interested in hearing from the community what you think as this is the culmination of a lot of effort from a lot of people across so many different fields (seriously, the number of folks across manufacturing, engineering, design, logistics, and marketing who…
2022 · its alternatives →
- 19
Irreverent overview of ideas in math, CS & philosophy
2016 · cambridge.org · its alternatives →
- 20OS
We’ve just released an open-source library for solving the Maximum Independent Set (MIS) problem with neutral atom quantum computing, running on both quantum processing units (QPUs) and classical hardware, thanks to emulators. This project is the result of collaboration between Pasqal, academic researchers, and industry partners, aiming to make it practical to experiment with quantum approaches to hard combinatorial optimization tasks. The MIS problem appears in real-world scenarios like scheduling, resource allocation, and network optimization, areas where classical solvers often struggle…
2025 · its alternatives →
- 21
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation. - PennyLaneAI/pennylane
2018 · github.com · its alternatives →
- 22
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling - GitHub - achillesrasquinha/bulbea: :boar: Deep Learning based Python Library for Stock Market Prediction and Modelling
2017 · github.com · its alternatives →
- 23
The model uses a 1024-dimensional complex Hilbert space with 32 layers of programmable Mach–Zehnder meshes (Reck architecture) and derives token probabilities directly via the Born rule. Despite using only unitary operations and no attention mechanism, a 1024×32 model achieves coherent TinyStories generation after < 1.8 hours of training on a single consumer GPU. This is Part 1 - the next step is physical implementation with $50 of optics from AliExpress.
Nov 2025 · zenodo.org · its alternatives →
- 24
Hello everyone! I've been working on this project for a few months as part of my thesis in Machine Learning. It's meant to be a library that provides an easy-to-use but flexible API to design and train Diffusion Models. I decided to make it because I wanted to quickly prototype a Diffusion Model but there were no good tools to do it with. I think it really can help people prototype their own Diffusion Models a lot faster and only in a few lines of code. The base idea is to have a Model class that takes different modules corresponding to the different aspects of the Diffusion Model process…
2023 · github.com · its alternatives →
Also compare
- filippo.io/mlkem768 – Post-Quantum Cryptography for the Go Ecosystem alternatives
- TensorFlow 1.0 alternatives
- Netmind Power alternatives
- My Book on Evolutionary Algorithms, Written in Python Notebooks alternatives
- Tensorflow Research Cloud alternatives
- Covalent – distributed computing for ML, HPC and Quantum (open source) alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →