2.2 Neural networks and deep learning Describing today's groundbreaking AI achievements, we have to realize that the underlying powerful deep learning approaches are based on neural network research conducted for many decades, motivated by the knowledge accumulated on the operation and functions of biolo...
(the “Whitepaper”) was accepted for the 2020 International Joint Conference on Neural Networks (IJCNN 2020), a flagship conference of the Computational Intelligence Society that covers a wide range of topics in the field of neural networks, from biological neural networks to a...
*Hebbian theory has been the primary basis for the conventional view that when analyzed from a holistic level,engrams are neuronal nets orneural networks. Additional ideas regarding cell assembly theory and its role in forming engrams, along the lines of the concept of auto-association, described...
there are not so many conversational AI research papers presented at NeurIPS 2020. Still, several papers from the main conference program focus on dialog systems, introducing new ways to:
View the complete list of NVIDIA Research accepted papers, workshop and tutorials, demos, and explore job opportunities at theNVIDIA at NeurIPS 2021website. Related resources GTC session:NVIDIA Graduate Fellowship Fast Forward Talks GTC session:Insights from NVIDIA Research ...
Spotlight papers Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators Spiking neural networks (SNNs) represent a promising approach to developing artificial neural networks that are both energy-efficient and biologically plausible. However, applying SNNs to sequential tasks...
Debackere,The emergence of a new technology: the case of neural networks. Working Paper WP3031-89-BPS, Alfred P. Sloan School of Management, Massachusetts Institute of Technology, Cambridge (MA), 1989. Google Scholar E. Valentine, Neurals nets: From Hartley and Hebb to Hinton,J. Math. ...
Classification of Research Papers on Radio Frequency Electromagnetic Field (RF-EMF) Using Graph Neural Networks (GNN)ELECTROMAGNETIC fieldsCONVOLUTIONAL neural networksRADIO frequencyNATURAL language processingSCIENTIFIC literatureSHIFT registersMULTISPECTRAL imagingThis study compares the performance of graph ...
NVIDIA Research is passionate about developing the technology and finding the breakthroughs that bring positive change to the world. Beyond publishing our work in papers and at conferences, we apply it to NVIDIA solutions and services, share resources and code, and offer hands-on experiences with ...
GNN latest papers **The latest research papers on graph representation learning** Key Keywords: Graph representation Learning, graph pooling, graph transformer Contents [Graph representation Learning](#Graph representation Learning) [Basic Models](#Basic Models) [graph pooling](#graph pooling) [graph...