Life & fun · alternatives · 2026
24 alternatives to Optimizing Higher Order Functions with Hypothetical Inverses
This is a Medium article from 2016 that explores techniques for optimizing higher order functions through the use of hypothetical inverses. It is aimed at software developers and computer scientists interested in… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Optimizing Higher Order Functions with Hypothetical Inverses launched in 2016; newer entries below may have overtaken it.
- 1
Faster user-land reimplementations for several common builtin native JavaScript functions. - codemix/fast.js
2014 · github.com · its alternatives →
- 2
Experimental Global Optimization Algorithm. Contribute to chrisstroemel/Simple development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 3
Recently I've been working on making LLM evaluations fast by using bayesian optimization to select a sensible subset. Bayesian optimization is used because it’s good for exploration / exploitation of expensive black box (paraphrase, LLM). I would love to hear your thoughts and suggestions on this!
2024 · github.com · its alternatives →
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A guide to functional programming
2016 · amazon.com · its alternatives →
- 5
Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equally complex. To tackle this problem, we introduce DeTikZify, a novel multimodal language model that automatically synthesizes scientific figures as semantics-preserving TikZ graphics programs based on sketches and existing figures. We also introduce a Monte Carlo Tree Search-based inference algorithm that enables DeTikZify to iteratively refine its…
2024 · github.com · its alternatives →
- 6
Experts' Approach to Optimization
2015 · amazon.com · its alternatives →
- 7
Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
2024 · github.com · its alternatives →
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Lift your conversion rate with repeatedly AB tested patterns
2018 · goodui.org · its alternatives →
- 10
This little project came about because I kept running into the same problem: cleanly differentiating sensor data before doing analysis. There are a ton of ways to solve this problem, I've always personally been a fan of using kalman filters for the job as its easy to get the double whammy of resampling/upsampling to a fixed consistent rate and also smoothing/outlier rejection. I wrote a little numpy only bayesian filtering/smoothing library recently (https://github.com/hugohadfield/bayesfilter/) so this felt like a fun and very useful first thing to…
2024 · github.com · its alternatives →
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It turns out the inverse of the Hessian of a deep net is easy to apply to a vector. Doing this naively takes cubically many operations in the number of layers (so impractical), but it's possible to do this in time linear in the number of layers (so very practical)! This is possible because the Hessian of a deep net has a matrix polynomial structure that factorizes nicely. The Hessian-inverse-product algorithm that takes advantage of this is similar to running backprop on a dual version of the deep net. It echoes an old idea of Pearlmutter's for computing Hessian-vector products. Maybe this…
Jan 2026 · github.com · its alternatives →
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A book on conversion rate optimization by ConversionXL
2015 · amazon.com · its alternatives →
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🎯 A comprehensive gradient-free optimization framework written in Python - 100/Solid
2017 · github.com · its alternatives →
- 15
Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
2019 · github.com · its alternatives →
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Clever solutions to classic programming problems
2015 · amazon.com · its alternatives →
- 17
Stephen Wolfram's new book on the Wolfram Language
2015 · wolfram.com · its alternatives →
- 18
The best of functional programming in your browser
2016 · changelog.com · its alternatives →
- 19
A unified interface for optimization algorithms and experiments - hyperactive-project/Hyperactive
2021 · github.com · its alternatives →
- 20
Zero-Knowledge Proofs (ZKPs) let an untrusted proved show that computation was executed correctly without revealing the inputs to the verifier. However to prove anything, the computation first has to be expressed as a circuit: a system of polynomial equations (constraints) over a finite field. Circuits are the assembly language of zk and every constraint costs prover (and sometimes verifier) time, so production circuits are aggressively hand-optimized. Over the last months, we have been experimenting with writing formal specifications instead and letting LLMs produce the circuits: as long as…
Jul 2026 · zk.golf · its alternatives →
- 21
See what it’s like to program in a language without null.
2015 · books.thoughtbot.com · its alternatives →
- 22
Improve the execution speed of pythonic paradigms.
2018 · medium.com · its alternatives →
- 23
Learn Go (Golang) by writing real code in this interactive course. Practice structs, interfaces, errors, concurrency, and idiomatic backend patterns.
2020 · qvault.io · its alternatives →
- 24
A high-level, high-performance dynamic programming language
2017 · julialang.org · its alternatives →
Also compare
- Fast.js – faster reimplementations of native JavaScript functions alternatives
- A radically more scalable alternative to Bayesian Optimization alternatives
- Faster LLM evaluation with Bayesian optimization alternatives
- Purely Functional Data Structures alternatives
- Synthesize TikZ Graphics Programs for Scientific Figures and Sketches alternatives
- Master The Essentials of Conversion Optimization 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 →