AIMC Topic: Learning

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Human shape representations are not an emergent property of learning to classify objects.

Journal of experimental psychology. General Sep 11, 2023
Humans are particularly sensitive to relationships between parts of objects. It remains unclear why this is. One hypothesis is that relational features are highly diagnostic of object categories and emerge as a result of learning to classify objects....
Humans Neural Networks, Computer Learning
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RepCo: Replenish sample views with better consistency for contrastive learning.

Neural networks : the official journal of the International Neural Network Society Sep 11, 2023
Contrastive learning methods aim to learn shared representations by minimizing distances between positive pairs, and maximizing distances between negative pairs in the embedding space. To achieve better performance of contrastive learning, one of the...
Neural Networks, Computer Learning Semantics
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A scalable second order optimizer with an adaptive trust region for neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 11, 2023
We introduce Tadam (Trust region ADAptive Moment estimation), a new optimizer based on the trust region of the second-order approximation of the loss using the Fisher information matrix. Despite the enhanced gradient estimations offered by second-ord...
Neural Networks, Computer Algorithms Learning Trust
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Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.

Biological cybernetics Sep 11, 2023
The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiolo...
Neural Networks, Computer Algorithms Learning Action Potentials Neurons
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iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease.

PLoS computational biology Sep 11, 2023
Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing e...
Brain Learning Deep Learning Records
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Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning.

Journal of chemical information and modeling Sep 5, 2023
Lead optimization supported by artificial intelligence (AI)-based generative models has become increasingly important in drug design. Success factors are reagent availability, novelty, and the optimization of multiple properties. Directed fragment-re...
Artificial Intelligence Databases, Factual Learning Chemistry, Pharmaceutical Libraries, Digital
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On exploring node-feature and graph-structure diversities for node drop graph pooling.

Neural networks : the official journal of the International Neural Network Society Sep 3, 2023
Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representations learning of GNNs, graph pooling...
Neural Networks, Computer Learning Natural Language Processing Social Networking
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Artificial intelligence-assisted dermatology diagnosis: From unimodal to multimodal.

Computers in biology and medicine Sep 1, 2023
Artificial Intelligence (AI) is progressively permeating medicine, notably in the realm of assisted diagnosis. However, the traditional unimodal AI models, reliant on large volumes of accurately labeled data and single data type usage, prove insuffic...
Humans Artificial Intelligence Learning Reproducibility of Results Health Facilities Dermatology
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Adaptive optimal control of affine nonlinear systems via identifier-critic neural network approximation with relaxed PE conditions.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2023
This paper considers an optimal control of an affine nonlinear system with unknown system dynamics. A new identifier-critic framework is proposed to solve the optimal control problem. Firstly, a neural network identifier is built to estimate the unkn...
Neural Networks, Computer Algorithms Computer Simulation Learning Nonlinear Dynamics
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Effects of Motion-Relevant Knowledge From Unlabeled Video to Human-Object Interaction Detection.

IEEE transactions on neural networks and learning systems Sep 1, 2023
The existing works on human-object interaction (HOI) detection usually rely on expensive large-scale labeled image datasets. However, in real scenes, labeled data may be insufficient, and some rare HOI categories have few samples. This poses great ch...
Humans Neural Networks, Computer Learning Knowledge Iodine Compounds
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