Toshihiko Yanase's starred repositories
customhys
Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators serve as building blocks for tailoring metaheuristics. They were extracted from ten well-known metaheuristics in the literature.
optunahub-web
Frontend of OptunaHub Registry
optunahub-registry
A registry of third-party Optuna packages
japanese-lm-fin-harness
Japanese Language Model Financial Evaluation Harness
flatline_lsp
Github Copilot-like LSP code completion server with local LLM powered by llama.cpp
optuna-dashboard
Real-time Web Dashboard for Optuna.
pytorch-pfn-extras
Supplementary components to accelerate research and development in PyTorch
deep-learning-from-scratch-5
『ゼロから作る Deep Learning ❺』(O'Reilly Japan, 2024)
awesome-japanese-llm
日本語LLMまとめ - Overview of Japanese LLMs
LambertProblem.jl
Julia code of Lambert's Problem
argo-workflows
Workflow Engine for Kubernetes
optuna-fast-fanova
Cython accelerated fANOVA implementation for Optuna.
optuna-cpp
Optuna C++ binding
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
optuna-examples
Examples for https://github.com/optuna/optuna
optuna-dashboard-feedstock
A conda-smithy repository for optuna-dashboard.