In-sensor reservoir computing for language learning via two-dimensional memristors

Structured clustering for memristive crossbar based neuromorphic architectures

Spiking neural network simulator based on memrisor characteristics

built Memristor model and simulated learning circuit with python

HSPICE implementation of hybrid CMOS/Memristor BAM

Crossbar Parasitics Simulator – A tool for benchmarking parasitic resistance models in RRAM crossbars and evaluating neural networks under realistic hardware constraints.

Production-ready framework for training robust computer vision models. Features multi-GPU support, EMA tracking, label smoothing, and comprehensive robustness evaluation across 4 noise types. Includes scalable TF.Data pipeline, automated testing, Docker support, and CLI tools. Install: pip install robust-vision

A solver for Memristor Crossbar Arrays