Disaggregating solar photovoltaics (PV) profiles from smart electricity meter data has attracted attention, as Distribution System Operators (DSOs) need street-level PV generation profiles to improve grid operations and planning. Given the importance of reliability in operational decisions, probabilistic results are pr...
Modern edge devices increasingly require real-time adaptation to their environment without relying on cloud-based updates, which can introduce latency and security risks. To meet these demands, memory-augmented neural networks (MANNs) have gained traction for enabling adaptive on-device learning. Hardware implementatio...
Changhoon Joe, K. Byun, Min-Seung Kang et al.· npj Unconventional Computing· 0 citations
The impact of memory frequency and computing frequency on DNN inference time is considered, and a low-complexity heuristic algorithm is proposed to effectively solve the overall problem with polynomial time complexity.
UVirtio introduces a device-profile-based virtual hardware abstraction layer that minimizes performance overhead, and implements a live migration mechanism using differential packing, providing a scalable and agile virtualization solution for the ubiquitous computing frontier.
Muliang Shou, Yufan Jiang, Tianlei Xiong et al.· ACM Transactions on Architec...· 0 citations
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SimpleCount is proposed, a reference with no parameter fitting that selects one scalar feature per dataset from a fixed pool of counts, recencies, first-occurrence indicators, and count-derived transforms that matches or exceeds SLADE on three of six datasets and exceeds IsoForest on all six.
An ADC/DAC-free neural accelerator based on the Walsh-Hadamard Transform and bit-plane processing that offers a multiplier-free, converter-free, regular, and scalable solution for low-power edge intelligence.
Srinivasa Reddy Dumpa, M. Rani, Edudula Manisha et al.· Adolescência e Saúde· 0 citations
With the transformation of unconventional oil and gas resource development towards digitalization and intelligence, massive, multi-source, and dynamic well-entry fluid and material detection data have become core assets driving engineering decision-making. Traditional digital platforms aimed at process onlineization ha...
Xue-Qiang Wang, Long Chen, Feng Xiong et al.· International Conference on...· 0 citations
A Green AI–driven framework is presented for optimizing machine learning models with the goal of supporting sustainable computing and offers a practical and reproducible solution for deploying energy-efficient machine learning models across both cloud and edge environments.
Vishal Prashant Malage, S. Pingale, Dhanashri Surwase· International journal of com...· 0 citations
Cameroon is made up of an extensive tectonic system that includes a geologically significant structure in Central Africa called the Cameroon Volcanic Line (CVL). In this study, a multi-phase approach was applied to identify new tectonic structures across the CVL using gravity data from the XGM2019e_2159 model, magnetic...
N. E. Ekolle· Geodynamics & Tectonophy...· 0 citations
This paper proposes a simple current-controlled second-order LAM mathematical model, which exhibits both negative differential resistance edge of chaos (EOC) domains and positive differential resistance (PDR) EOC domains, and constructs a minimalist third-order neuronal circuit by simply paralleling the LAM with a capa...
Zhen-Zhou Lu, Xinyi Wang, Zhi Zeng et al.· Chinese Physics B· 0 citations
It is shown that edge symmetries can be exploited to design syndrome-extraction circuits from the underlying components, rather than from the full quantum code, to produce depth-optimal circuits from the underlying components.
M. Nguyen, M. Rimbach-Russ, S. Bosco· 1 citation· ⚡1
FedMARL-LTI is presented, a federated multi-agent reinforcement learning framework whose architecture answers both pressures with a single decision: each organization’s threat intelligence is shared only as a differentially private 768-dimensional semantic embedding, never as raw data.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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