AI · alternatives · 2026

24 alternatives to Train a Convolutional Neural Nets Using Multi-Party Computation

Most efforts to privately train machine-learning models either use homomorphic encryption or secure multi-party computation (MPC). Recent insights indicate…

This project demonstrates how to train convolutional neural networks using secure multi-party computation (MPC), specifically the SPDZ protocol. It addresses private machine learning by enabling neural network training… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. Train a Convolutional Neural Nets Using Multi-Party Computation launched in 2018; newer entries below may have overtaken it.

1IM
I made a neural net that analyzes privacy policies▲502
2019 · useguard.com · its alternatives →
2
Thinc, a new deep learning library by the makers of spaCy and FastAPI▲250
Thinc is a lightweight type-checked deep learning library for composing models, with support for layers defined in frameworks like PyTorch and TensorFlow.
2020 · thinc.ai · its alternatives →
3
I invented a new generative model and got accepted to ICLR▲656
I invented Discrete Distribution Networks, a novel generative model with simple principles and unique properties, and the paper has been accepted to ICLR2025! Modeling data distribution is challenging; DDN adopts a simple yet fundamentally different approach compared to mainstream generative models (Diffusion, GAN, VAE, autoregressive model): 1. The model generates multiple outputs simultaneously in a single forward pass, rather than just one output. 2. It uses these multiple outputs to approximate the target distribution of the training data. 3. These outputs together represent a discrete…
2025 · discrete-distribution-networks.github.io · its alternatives →
4
A perceptron with stochastic gradient descent in Go▲94
A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
5
ArcaneVM – A Fully Homomorphic Encryption Brainfuck Virtual Machine▲131
A Fully Homomorphic Encryption Brainfuck virtual machine - f-prime/arcanevm
2019 · github.com · its alternatives →
6
Netmind Power▲272
Hi 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 →
7
Encrypted Deep Learning Classification with PyTorch and PySyft▲10
Update as of November 18, 2021: The version of PySyft mentioned in this post has been deprecated. Any implementations using this older version of PySyft are…
2019 · blog.openmined.org · its alternatives →
8GC
Graph Convolutional Networks – Intro to neural networks on graphs▲106
Many important real-world datasets come in the form of graphs or networks: social networks, knowledge graphs, protein-interaction networks, the World Wide Web, etc. (just to name a few). Yet, until recently, very little attention has been devoted to the generalization of neural...
2016 · tkipf.github.io · its alternatives →
9
Fast Deep Reinforcement Learning Course▲148
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series. Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all). I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun. This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to…
2022 · courses.dibya.online · its alternatives →
10
Multi-GPU Reinforcement Learning in Tensorflow for OpenAI Gym▲58
Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn
2016 · github.com · its alternatives →
11
A competition for small neural networks that play strategy gamesfree▲116
A ranked ladder for small neural networks that play strategy games. Train a model, write an adapter, upload two files, and get measured into a weight class from 8 KiB up.
Sep 2026 · tinybrains.dev · its alternatives →
12
Logistic Regression Training on Encrypted Data with FHE▲8
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks. - concrete-ml/docs/advanced_examples/LogisticRegressionTraining.ipynb at release/1.4.x · zama-ai/concrete-ml
2024 · github.com · its alternatives →
13N5
NN-512 – Generate standalone C code for neural nets▲111
2020 · nn-512.com · its alternatives →
14
Neural Networks and Deep Learning▲95
Core concepts behind neural networks and deep learning
2015 · neuralnetworksanddeeplearning.com · its alternatives →
15
I am a high school student and I did research on 3D adversarial attacks▲116
Abstract page for arXiv paper 1908.06062: Adversarial shape perturbations on 3D point clouds
2019 · arxiv.org · its alternatives →
16
A completely handwritten deep neural network in python▲13
A handwritten multilayer perceptron classifer using numpy. - meetvora/mlp-classifier
2016 · github.com · its alternatives →
17
Using 3D Convolutional Neural Networks for Speaker Verification▲59
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification - astorfi/3D-convolutional-speaker-recognition
2017 · github.com · its alternatives →
18
Tensorflow implementation of Conditional PixelCNN▲56
Tensorflow implementation of Gated Conditional Pixel Convolutional Neural Network - anantzoid/Conditional-PixelCNN-decoder
2016 · github.com · its alternatives →
19
Building an End-to-End Encrypted Shazam with Homomorphic Encryption▲59
A tutorial on how to code a privacy-preserving version of Shazam using Zama Concrete ML.
2024 · zama.ai · its alternatives →
20
Monostate AItraining▲59
Fine-tuning, RL, and inference in one CLI
Dec 2025 · github.com · its alternatives →
21
Generating Collisions on NeuralHash▲22
Proof of Concept : generating collisions on a neural perceptual hash - collisionLSH.py
2021 · gist.github.com · its alternatives →
22
Encrypted Deep Learning in PyTorch▲37
Perform data science on data that remains in someone else's server - OpenMined/PySyft
2018 · github.com · its alternatives →
23
Deep learning without gradient descent, 500 layers, no skip connections▲5
Code that reproduces experiments from a scientific paper - xolod7/polyharmonic-cascade
Jan 2026 · github.com · its alternatives →
24IC
I co-wrote a book on training Deep Learning models in Go▲45
A friend and I wrote a book on how to build and train Deep Learning models in Go. We wanted it to be a useful reference for deep learning basics for Go programmers. Deep Learning is slowly seeping into everything we use every day and we thought it would be great if more people could do it in Go. The book is available here and on Amazon as well. https://www.packtpub.com/big-data-and-business-intelligence/hands-deep-learning-go We would appreciate any feedback and we're always looking to improve.
2019 · its alternatives →

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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 →