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Top 14 Python automatic-differentiation Projects
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AppSignal
Monitoring that respects your time & budget. APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
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pennylane
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.
Project mention: AWS Summit Bogotá 2026: Paradigmas agénticos, resiliencia multirregión y seguridad declarativa | dev.to | 2026-08-05 -
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Project mention: PennyLane is an open-source quantum software platform for quantum | news.ycombinator.com | 2026-07-17
For those interested in compilers/LLVM/MLIR, the underlying compiler (Catalyst) may also be interesting: https://github.com/pennylaneai/catalyst
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Project mention: Tesseract Core: Universal components for differentiable scientific computing | news.ycombinator.com | 2026-07-16
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Project mention: TensorCircuit-NG vs cuQuantum on H200: JIT compilation beats the "magic GPU library" assumption | dev.to | 2026-06-06
We used the workload as in the script for 1D TFIM VQE task:
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Project mention: Show HN: Advect – autodiff for NumPy and Array API programs | news.ycombinator.com | 2026-08-11
I built Advect, an automatic differentiation library for scientific Python. It provides broad NumPy API coverage, follows the Python Array API standard, and works with ordinary Python functions.
In addition to dynamic differentiation, Advect can stage a function into a reusable program that can be optimized, differentiated again, serialized, and loaded later. There is also some support for SciPy, xarray, and interoperability with other autodiff frameworks.
The linked playground runs entirely in the browser through Pyodide, so you can try tracing and differentiating an expression without installing anything.
The first public release is available with pip install advect.
Source: https://github.com/yaugenst/advect
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memoized_coduals
Shows that it is possible to implement reverse mode autodiff using a variation on the dual numbers called the codual numbers
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adiabatic-silicon-aging-guard
Experimental 3-tier silicon failure-fencing engine isolating volatile NaN/Inf bleeding via runtime CPython method table interception and timing-frozen JAX shard_map topologies.
Project mention: Show HN: Overcoming silicon-level aging through fault tolerance (PoC) | news.ycombinator.com | 2026-08-19 -
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Python automatic-differentiation discussion
Python automatic-differentiation related posts
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AWS Summit Bogotá 2026: Paradigmas agénticos, resiliencia multirregión y seguridad declarativa
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PennyLane is an open-source quantum software platform for quantum
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Tesseract Core: Universal components for differentiable scientific computing
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List of free Quantum Toolkits
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LLMs on your local Computer (Part 1)
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Show HN: Elodin – A better framework for physics simulation
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Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Oct 2026
Index
What are some of the best open-source automatic-differentiation projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | autograd | 7,539 |
| 2 | pennylane | 3,489 |
| 3 | JAXFLUIDS | 653 |
| 4 | torchopt | 638 |
| 5 | catalyst | 238 |
| 6 | neograd | 236 |
| 7 | torchquad | 229 |
| 8 | tesseract-core | 135 |
| 9 | tensorcircuit-ng | 92 |
| 10 | tensortrax | 11 |
| 11 | advect | 9 |
| 12 | slope-ad | 7 |
| 13 | memoized_coduals | 3 |
| 14 | adiabatic-silicon-aging-guard | 1 |