Gaussian process regression for materials and molecules

VL Deringer, AP Bartók, N Bernstein… - Chemical …, 2021 - ACS Publications
We provide an introduction to Gaussian process regression (GPR) machine-learning
methods in computational materials science and chemistry. The focus of the present review …

A survey of network anomaly detection techniques

M Ahmed, AN Mahmood, J Hu - Journal of Network and Computer …, 2016 - Elsevier
Abstract Information and Communication Technology (ICT) has a great impact on social
wellbeing, economic growth and national security in todays world. Generally, ICT includes …

Bertscore: Evaluating text generation with bert

T Zhang, V Kishore, F Wu, KQ Weinberger… - arxiv preprint arxiv …, 2019 - arxiv.org
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to
common metrics, BERTScore computes a similarity score for each token in the candidate …

Deepsdf: Learning continuous signed distance functions for shape representation

JJ Park, P Florence, J Straub… - Proceedings of the …, 2019 - openaccess.thecvf.com
Computer graphics, 3D computer vision and robotics communities have produced multiple
approaches to representing 3D geometry for rendering and reconstruction. These provide …

Graph neural networks: foundation, frontiers and applications

L Wu, P Cui, J Pei, L Zhao, X Guo - … of the 28th ACM SIGKDD Conference …, 2022 - dl.acm.org
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

From word embeddings to document distances

M Kusner, Y Sun, N Kolkin… - … conference on machine …, 2015 - proceedings.mlr.press
Abstract We present the Word Mover's Distance (WMD), a novel distance function between
text documents. Our work is based on recent results in word embeddings that learn …

Visualizing structure and transitions in high-dimensional biological data

KR Moon, D Van Dijk, Z Wang, S Gigante… - Nature …, 2019 - nature.com
The high-dimensional data created by high-throughput technologies require visualization
tools that reveal data structure and patterns in an intuitive form. We present PHATE, a …

[CITATION][C] Learning OpenCV: Computer vision with the OpenCV library

G Bradski - O'REILLY google schola, 2008 - books.google.com
" This library is useful for practitioners, and is an excellent tool for those entering the field: it
is a set of computer vision algorithms that work as advertised."-William T. Freeman …

Sliced wasserstein discrepancy for unsupervised domain adaptation

CY Lee, T Batra, MH Baig… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
In this work, we connect two distinct concepts for unsupervised domain adaptation: feature
distribution alignment between domains by utilizing the task-specific decision boundary and …

Image retrieval: Ideas, influences, and trends of the new age

R Datta, D Joshi, J Li, JZ Wang - ACM Computing Surveys (Csur), 2008 - dl.acm.org
We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …