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Learning

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Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm.

Evolutionary computation Jun 1, 2022
An important challenge in reinforcement learning is to solve multimodal problems, where agents have to act in qualitatively different ways depending on the circumstances. Because multimodal problems are often too difficult to solve directly, it is of...
Algorithms Learning Robotics Problem Solving Biological Evolution
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Federated Learning in Healthcare: A Privacy Preserving Approach.

Studies in health technology and informatics May 25, 2022
A need to enhance healthcare sector amidst pandemic arises. Many technological developments in Artificial Intelligence (AI) are being constantly leveraged in different fields of healthcare. One such advancement, Federated Learning(FL) has acquired re...
Artificial Intelligence Delivery of Health Care Learning Health Facilities Privacy
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To make AI fair, here's what we must learn to do.

Nature May 1, 2022
Artificial Intelligence Learning
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Understanding the Computational Demands Underlying Visual Reasoning.

Neural computation Apr 15, 2022
Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual reasoning. We do this by systematically assessing the ability of modern d...
Humans Neural Networks, Computer Learning Problem Solving
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Desynchronous learning in a physics-driven learning network.

The Journal of chemical physics Apr 14, 2022
In a neuron network, synapses update individually using local information, allowing for entirely decentralized learning. In contrast, elements in an artificial neural network are typically updated simultaneously using a central processor. Here, we in...
Neural Networks, Computer Computer Simulation Learning Neurons Physics
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Learning to represent continuous variables in heterogeneous neural networks.

Cell reports Apr 5, 2022
Animals must monitor continuous variables such as position or head direction. Manifold attractor networks-which enable a continuum of persistent neuronal states-provide a key framework to explain this monitoring ability. Neural networks with symmetri...
Neural Networks, Computer Brain Learning Animals Models, Neurological Neurons
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Understanding Dynamics of Nonlinear Representation Learning and Its Application.

Neural computation Mar 23, 2022
Representations of the world environment play a crucial role in artificial intelligence. It is often inefficient to conduct reasoning and inference directly in the space of raw sensory representations, such as pixel values of images. Representation l...
Neural Networks, Computer Artificial Intelligence Algorithms Learning
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A robust and scalable graph neural network for accurate single-cell classification.

Briefings in bioinformatics Mar 10, 2022
Single-cell RNA sequencing (scRNA-seq) techniques provide high-resolution data on cellular heterogeneity in diverse tissues, and a critical step for the data analysis is cell type identification. Traditional methods usually cluster the cells and manu...
Neural Networks, Computer Algorithms Learning Single-Cell Analysis Sequence Analysis, RNA Exome Sequencing
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From photos to sketches - how humans and deep neural networks process objects across different levels of visual abstraction.

Journal of vision Feb 1, 2022
Line drawings convey meaning with just a few strokes. Despite strong simplifications, humans can recognize objects depicted in such abstracted images without effort. To what degree do deep convolutional neural networks (CNNs) mirror this human abilit...
Humans Neural Networks, Computer Learning Concept Formation Visual Perception Recognition, Psychology
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Learning representation for multiple biological networks via a robust graph regularized integration approach.

Briefings in bioinformatics Jan 17, 2022
Learning node representation is a fundamental problem in biological network analysis, as compact representation features reveal complicated network structures and carry useful information for downstream tasks such as link prediction and node classifi...
Neural Networks, Computer Computer Simulation Learning Diffusion
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