Results 81 to 90 of about 9,750,100 (244)

An Introduction to Machine Learning

Clinical Pharmacology & Therapeutics, 2020
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever‐increasing amount of data and computational power as well as the discovery of improved learning algorithms. However, the idea of a computer learning some abstract concept from data and applying them to yet unseen ...
Solveig Badillo, Balazs Banfai, Fabian Birzele, Iakov I. Davydov, Lucy Hutchinson, Tony Kam‐Thong, Juliane Siebourg‐Polster, Bernhard Steiert, Jitao David Zhang   +8 more
openaire   +3 more sources

Diversity in Machine Learning [PDF]

IEEE Access, 2019
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine learning system is composed of plentiful training data, a good model training process, and an accurate inference.
Zhiqiang Gong, Ping Zhong, Weidong Hu
openaire   +4 more sources

Physics-informed machine learning

Nature Reviews Physics, 2021
G. Karniadakis, I. Kevrekidis, Lu Lu, P. Perdikaris, Sifan Wang, Liu Yang   +5 more
semanticscholar   +1 more source

Industrial Machine Learning Is Not Academic Machine Learning

, 2018
State Treasury Office of Ceara – Fortaleza, CE ...
openaire   +1 more source

Accelerating crystal structure search through active learning with neural networks for rapid relaxations

npj Computational Materials
Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space.
Stefaan S. P. Hessmann, Kristof T. Schütt, Niklas W. A. Gebauer, Michael Gastegger, Tamio Oguchi, Tomoki Yamashita   +5 more
doaj   +1 more source

3D scattering transforms for disease classification in neuroimaging

NeuroImage: Clinical, 2017
Classifying neurodegenerative brain diseases in MRI aims at correctly assigning discrete labels to MRI scans. Such labels usually refer to a diagnostic decision a learner infers based on what it has learned from a training sample of MRI scans ...
Tameem Adel, Taco Cohen, Matthan Caan, Max Welling   +3 more
doaj   +1 more source

A Probabilistic Adversarial Autoencoder for Novelty Detection: Leveraging Lightweight Design and Reconstruction Loss

IEEE Access
A novelty detection task involves identifying whether a data point is an outlier, given a training dataset that primarily captures the distribution of inliers. The novel class is usually absent, poorly sampled, or not well defined in the training data. A
Muhammad Asad, Ihsan Ullah, Muhammad Adeel Hafeez, Ganesh Sistu, Michael G. Madden   +4 more
doaj   +1 more source

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

Nature Communications, 2019
Machine learning models can accurately predict atomistic chemical properties but do not provide access to the molecular electronic structure. Here the authors use a deep learning approach to predict the quantum mechanical wavefunction at high efficiency ...
K. T. Schütt, M. Gastegger, A. Tkatchenko, K.-R. Müller, R. J. Maurer   +4 more
doaj   +1 more source

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

, 2014
Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest.
Aparna Lakshmiratan, Carlos Garcia, David Chickering, David Grangier, Denis Charles, Jina Suh, Johan Verwey, Jurado Suarez, Léon Bottou, Patrice Simard, Saleema Amershi   +10 more
core  

Is it ethical to avoid error analysis?

, 2017
Machine learning algorithms tend to create more accurate models with the availability of large datasets. In some cases, highly accurate models can hide the presence of bias in the data.
García-Martín, Eva, Lavesson, Niklas
core