ivan-vasilev/neuralnetworks

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1236 stars · 347 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Java library implementing deep learning algorithms and deep neural network architectures (MLPs, CNNs, RBMs, autoencoders, DBNs) with GPU acceleration via OpenCL and Aparapi. It supports training algorithms like backpropagation and contrastive divergence with greedy layer-wise training.

Use cases

• train deep neural networks in java
• gpu-accelerated neural network training on jvm
• implement convolutional networks in java
• learn deep learning algorithms from java code
• train autoencoders and deep belief networks
• run backpropagation with dropout on gpu

When to choose

• you need deep learning in pure Java on the JVM
• you want GPU acceleration via OpenCL without native deep learning stacks
• you want a small, readable codebase for studying deep learning algorithms

When to avoid

• you need a maintained, production-ready deep learning framework
• you need modern architectures like transformers or recurrent networks
• you need ecosystem support, documentation, or community updates - the project is inactive since 2017

Facets

library · maturity abandoned

deep-learning machine-learning gpu-computing deep-learning machine-learning gpu-computing jvm cross-platform neural-networks opencl aparapi convolutional-networks backpropagation mnist java gpu

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markdown · JSON · MCP: product_card(name="ivan-vasilev/neuralnetworks")