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szagoruyko/wide-residual-networks

3.8% and 18.3% on CIFAR-10 and CIFAR-100 observed · 2026-08-28

github.com/szagoruyko/wide-residual-networks · homepage · Lua · BSD-2-Clause (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3760
  • days_rel: n/a
  • days_push: 2570
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1315 stars · 301 forks observed · 2026-08-28

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

Reference implementation of Wide Residual Networks (WRN), a ResNet variant that trades depth for width to train faster and achieve state-of-the-art CIFAR, SVHN, COCO, and ImageNet results. Written in Lua for the Torch framework, with pretrained models later integrated into torchvision.

Use cases

  • train wide residual networks on CIFAR-10 and CIFAR-100
  • reproduce BMVC 2016 WRN paper results
  • get a faster alternative to very deep ResNets for image classification
  • benchmark new architectures against WRN baselines
  • load pretrained WRN ImageNet models via PyTorch Hub

When to choose

  • you need the original WRN training code for research reproduction
  • you want a strong, fast image classification baseline on CIFAR/SVHN
  • you are studying residual network architecture design

When to avoid

  • you need actively maintained code - the repo is legacy Torch/Lua and no longer developed
  • you want pretrained WRNs in a modern framework - use torchvision's wide_resnet50_2 instead
  • you need production deployment tooling

Facets

library · maturity maintenance

machine-learning deep-learning image-processing deep-learning computer-vision machine-learning lua residual-networks cifar torch research-code image-classification gpu

6 sources

Member repositories

RepositoryRoleHealth v2
szagoruyko/wide-residual-networksmain32

For agents

markdown · JSON · MCP: product_card(name="szagoruyko/wide-residual-networks")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem