AIMC Topic:
Computer Simulation

Clear Filters Showing 2141 to 2150 of 3855 articles

Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder.

BioMed research international
Computational drug repositioning, designed to identify new indications for existing drugs, significantly reduced the cost and time involved in drug development. Prediction of drug-disease associations is promising for drug repositioning. Recent years...

Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach.

ACS combinatorial science
There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. He...

A Stacked BiLSTM Neural Network Based on Coattention Mechanism for Question Answering.

Computational intelligence and neuroscience
Deep learning is the crucial technology in intelligent question answering research tasks. Nowadays, extensive studies on question answering have been conducted by adopting the methods of deep learning. The challenge is that it not only requires an ef...

The What-If Tool: Interactive Probing of Machine Learning Models.

IEEE transactions on visualization and computer graphics
A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an open-source application that allows practitioners t...

From Discrete to Continuous Modeling of Lymphocyte Development and Plasticity in Chronic Diseases.

Frontiers in immunology
The molecular events leading to differentiation, development, and plasticity of lymphoid cells have been subject of intense research due to their key roles in multiple pathologies, such as lymphoproliferative disorders, tumor growth maintenance and c...

Visual Interaction with Deep Learning Models through Collaborative Semantic Inference.

IEEE transactions on visualization and computer graphics
Automation of tasks can have critical consequences when humans lose agency over decision processes. Deep learning models are particularly susceptible since current black-box approaches lack explainable reasoning. We argue that both the visual interfa...

Stochasticity from function - Why the Bayesian brain may need no noise.

Neural networks : the official journal of the International Neural Network Society
An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing. Since the precise statistical p...

Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory.

Chemosphere
Accurate in silico predictions of chemical substance ecotoxicity has become an important issue in recent years. Most conventional methods, such as the Ecological Structure-Activity Relationship (ECOSAR) model, cluster chemical substances empirically ...

Force classification during robotic interventions through simulation-trained neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Intravitreal injection is among the most frequent treatment strategies for chronic ophthalmic diseases. The last decade has seen a serious increase in the number of intravitreal injections, and with it, adverse effects and drawbacks. To tack...

Obstacle effects on electrocommunication with applications to object detection of underwater robots.

Bioinspiration & biomimetics
Some fish species communicate electrically (termed electrocommunication) in turbid waters where other communication modalities fail. Inspired by this biological phenomenon, we have developed an artificial electrocommunication system for underwater ro...