Nature Search

Closed-form feedback-free learning with forward projection

Forward Projection (FP) trains neural networks with a single forward pass. It achieves competitive accuracy while offering interpretable hidden representations that reveal clinically relevant features.

Robert O’Shea
Bipin Rajendran
ResearchOpen Access05 Feb 2026
Nature Communications

Volume: 17, P: 1-10
Controlled oxygen vacancy electrode reservoir for robust WO₃-based memory devices

Oxide-based memristors hold potential for energy-efficient neuromorphic hardware in ‘Internet of Things’ applications, yet optimizing performance with CMOS-compatible low-temperature fabrication is challenging. Here, the authors employ a dual-function electrode strategy using an oxygen vacancy reservoir in an ITO/WO₃/TiN system, achieving enhanced memristive and synaptic performance, paving the way for advanced neuromorphic applications.

Ziyi Yuan
Babak Bakhit
Judith Louise MacManus-Driscoll
ResearchOpen Access06 Apr 2026
Communications Materials

P: 1-13
Neuromorphic computing with multi-memristive synapses

Memristive technology is a promising avenue towards realizing efficient non-von Neumann neuromorphic hardware. Boybat et al. proposes a multi-memristive synaptic architecture with a counter-based global arbitration scheme to address challenges associated with the non-ideal memristive device behavior.

Irem Boybat
Manuel Le Gallo
Evangelos Eleftheriou
ResearchOpen Access28 Jun 2018
Nature Communications

Volume: 9, P: 1-12
Accurate deep neural network inference using computational phase-change memory

Designing deep learning inference hardware based on in-memory computing remains a challenge. Here, the authors propose a strategy to train ResNet-type convolutional neural networks which results in reduced accuracy loss when transferring weights to in-memory computing hardware based on phase-change memory.

Vinay Joshi
Manuel Le Gallo
Evangelos Eleftheriou
ResearchOpen Access18 May 2020
Nature Communications

Volume: 11, P: 1-13
Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

S. R. Nandakumar
Irem Boybat
Bipin Rajendran
ResearchOpen Access15 May 2020
Scientific Reports

Volume: 10, P: 1-11
Ultra-low power neuromorphic obstacle detection using a two-dimensional materials-based subthreshold transistor

Kartikey Thakar
Bipin Rajendran
Saurabh Lodha
ResearchOpen Access18 Sept 2023
npj 2D Materials and Applications

Volume: 7, P: 1-10
Novel synaptic memory device for neuromorphic computing

Saptarshi Mandal
Ammaarah El-Amin
Rashmi Jha
ResearchOpen Access18 Jun 2014
Scientific Reports

Volume: 4, P: 1-10

Search

Filter By:

Closed-form feedback-free learning with forward projection

Controlled oxygen vacancy electrode reservoir for robust WO3-based memory devices

Neuromorphic computing with multi-memristive synapses

Accurate deep neural network inference using computational phase-change memory

Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

Ultra-low power neuromorphic obstacle detection using a two-dimensional materials-based subthreshold transistor

Novel synaptic memory device for neuromorphic computing

Search

Quick links

Controlled oxygen vacancy electrode reservoir for robust WO₃-based memory devices