AIMC Topic: Computer Graphics

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From GPUs to AI and quantum: three waves of acceleration in bioinformatics.

Drug discovery today
The enormous growth in the amount of data generated by the life sciences is continuously shifting the field from model-driven science towards data-driven science. The need for efficient processing has led to the adoption of massively parallel acceler...

Molecular Docking Improved with Human Spatial Perception Using Virtual Reality.

IEEE transactions on visualization and computer graphics
Adaptive steered molecular dynamics (ASMD) is a computational biophysics method in which an external force is applied to a selected set of atoms or a specific reaction coordinate to induce a particular molecular motion. Virtual reality (VR) based met...

A novel interactive deep cascade spectral graph convolutional network with multi-relational graphs for disease prediction.

Neural networks : the official journal of the International Neural Network Society
Graph neural networks (GNNs) have recently grown in popularity for disease prediction. Existing GNN-based methods primarily build the graph topological structure around a single modality and combine it with other modalities to acquire feature represe...

Visualizing and Comparing Machine Learning Predictions to Improve Human-AI Teaming on the Example of Cell Lineage.

IEEE transactions on visualization and computer graphics
We visualize the predictions of multiple machine learning models to help biologists as they interactively make decisions about cell lineage-the development of a (plant) embryo from a single ovum cell. Based on a confocal microscopy dataset, tradition...

Automated model building and protein identification in cryo-EM maps.

Nature
Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs. Here we present ModelAngelo, a machine-learning approa...

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization.

IEEE transactions on visualization and computer graphics
Since 2016, we have witnessed the tremendous growth of artificial intelligence+visualization (AI+VIS) research. However, existing survey articles on AI+VIS focus on visual analytics and information visualization, not scientific visualization (SciVis)...

Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

IEEE transactions on visualization and computer graphics
Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysis by transferring labels from a previously-annotated dataset to a new dataset. However, label transfer by end-to-end computational methods is challeng...

Visual Comparison of Language Model Adaptation.

IEEE transactions on visualization and computer graphics
Neural language models are widely used; however, their model parameters often need to be adapted to the specific domains and tasks of an application, which is time- and resource-consuming. Thus, adapters have recently been introduced as a lightweight...

Deep Learning for HDR Imaging: State-of-the-Art and Future Trends.

IEEE transactions on pattern analysis and machine intelligence
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years, there has been a significant advancement in HDR imag...

A Unified Understanding of Deep NLP Models for Text Classification.

IEEE transactions on visualization and computer graphics
The rapid development of deep natural language processing (NLP) models for text classification has led to an urgent need for a unified understanding of these models proposed individually. Existing methods cannot meet the need for understanding differ...