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nschaetti/EchoTorch ★ 502 117 APPLICATION

EchoTorch is a research-oriented PyTorch library for reservoir computing, specifically Echo State Networks (ESNs) and conceptors. It provides a comprehensive set of ESN variants (DeepESN, LiESN, GatedESN, StackedESN, etc.), conceptor-based learning and pattern generation, along with a custom `TimeTensor` wrapper that tracks time dimensions through PyTorch operations. The library includes synthetic dataset generators for time-series benchmarks (NARMA, Mackey-Glass, Lorenz, periodic signals), utilities for matrix generation, hyperparameter optimization, and reproduction scripts for several academic papers. The codebase is extensive but shows signs of age: it relies on deprecated PyTorch APIs (e.g., `torch.autograd.Variable`), has duplicate dataset packages (`datasetspy2`), and includes many stub or incomplete modules. It is intended for research experimentation, not production deployment.

RATING: 5.7/10 MAINT: stale DRIFT: high
#reservoir-computing #echo-state-network #conceptors #pytorch #time-series #research-library #python #python-toolkit #echo-state-networks #torch #machine-learning #machine-learning-algorithms #machinelearning #artificial-intelligence #artificial-neural-networks #neural-networks #recurrent-neural-networks #recurrent-networks
▸ 3 reusable components found
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