4 papers · 1 filter
An Open-Source LFSR-Based Stochastic Leaky Integrate-and-Fire Neuron in SkyWater 130 nm: Design, Stochastic Characterisation, and Rate Coding
Poornima Kumaresan, Santhosh Sivasubramani
Stochastic spiking neurons trade exact arithmetic for controlled randomness, lowering area and tolerating input noise, which suits event-driven edge hardware. We present a compact,…
Design and Development of a Neuromorphic Silicon Suite: PVT Sensing, Stochastic LIF Inference, On-Chip STDP Learning, and Crossbar Programming
Poornima Kumaresan, Santhosh Sivasubramani
Edge neuromorphic systems need compact, configurable hardware that combines probabilistic inference, local learning, and an interface to emerging analogue memory. We present four i…
Eliminating Vendor Lock-In in Quantum Machine Learning via Framework-Agnostic Neural Networks
Poornima Kumaresan, Shwetha Singaravelu, Lakshmi Rajendran +1
Quantum machine learning (QML) stands at the intersection of quantum computing and artificial intelligence, offering the potential to solve problems that remain intractable for cla…
Adaptive Tensor Network Simulation via Entropy-Feedback PID Control and GPU-Accelerated SVD
Harshni Kumaresan, Gayathri Muruganantham, Lakshmi Rajendran +1
Tensor network methods, particularly those based on Matrix Product States (MPS), provide a powerful framework for simulating quantum many-body systems. A persistent computational c…