Results 61 to 70 of about 4,929,609 (209)
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Advanced Intelligent Systems, EarlyView.Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
Graph Pattern Matching: From Intractable to Polynomial Time [PDF]
, 2010 Graph pattern matching is typically defined in terms of sub-graph isomorphism, which makes it an np-complete problem. Moreover, it requires bijective functions, which are often too restrictive to characterize patterns in emerging applications. We propose
Li, Jianzhong +5 more
core
Uncertain Attribute Graph Sub-Graph Isomorphism and its Determination Algorithm [PDF]
, 2014 The expectative sub-graph isomorphism of uncertain attribute graph is based on the analysis of complex network structure and the characteristic of uncertain attribute graph.
Zhang, Chunying, Zhao, Yanjun
core +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
Advanced Intelligent Systems, EarlyView.A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
A Graph Isomorphism Network with Weighted Multiple Aggregators for Speech Emotion Recognition
Interspeech 2022, 2022 Speech emotion recognition (SER) is an essential part of human-computer interaction. In this paper, we propose an SER network based on a Graph Isomorphism Network with Weighted Multiple Aggregators (WMA-GIN), which can effectively handle the problem of information confusion when neighbour nodes' features are aggregated together in GIN structure ...
Ying Hu 0005 +3 more
openaire +3 more sources
Integrating Products, Processes, and Sourcing for Eco‐Innovation
Business Strategy and the Environment, EarlyView.ABSTRACT Eco‐innovation research has often examined regulatory or technological drivers but has paid limited attention to how long‐term organizational change shapes eco‐innovation in mature, resource‐intensive industries. This study addresses that gap by investigating how two leading Finnish pulp and paper firms integrated product, process, and ...
Misa Bakajic, Anand Nair, Markku Kuula
wiley +1 more source
Distributed Graph Simulation: Impossibility and Possibility [PDF]
, 2014 This paper studies fundamental problems for distributed graph simulation. Given a pattern query Q and a graph G that is fragmented and distributed, a graph simulation algorithm A is to compute the matches Q(G) of Q in G.
Wang, Xin +3 more
core
IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification
CoRR, 2019 Deep learning models have achieved huge success in numerous fields, such as computer vision and natural language processing. However, unlike such fields, it is hard to apply traditional deep learning models on the graph data due to the 'node-orderless' property.
Lin Meng 0003, Jiawei Zhang 0001
openaire +2 more sources
Who Cares About Carbon Performance Strategy? Ownership Structure as a Driver for Carbon Performance
Business Strategy and the Environment, EarlyView.ABSTRACT This research aims to highlight the empirical, theoretical, and corporate governance arguments employed in the academic literature that examines ownership structure as a determinant of carbon performance—a key element in contemporary climate governance frameworks.
Thicia Stela Lima Sampaio +2 more
wiley +1 more source
Chemie Ingenieur Technik, EarlyView.This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn +5 more
wiley +1 more source