| Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead |
160 |
| The global landscape of AI ethics guidelines |
66 |
| Long short-term memory networks in memristor crossbar arrays |
50 |
| Designing neural networks through neuroevolution |
43 |
| Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction |
39 |
| Deep-learning cardiac motion analysis for human survival prediction |
34 |
| Deep learning optoacoustic tomography with sparse data |
28 |
| Reconstructing quantum states with generative models |
26 |
| Pathologist-level interpretable whole-slide cancer diagnosis with deep learning |
25 |
| In situ training of feed-forward and recurrent convolutional memristor networks |
23 |
| Reinforcement learning in artificial and biological systems |
22 |
| Principles alone cannot guarantee ethical AI |
19 |
| Fully portable and wireless universal brain-machine interfaces enabled by flexible scalp electronics and deep learning algorithm |
16 |
| Learning with known operators reduces maximum error bounds |
14 |
| Towards algorithmic analytics for large-scale datasets |
13 |
| The need for uncertainty quantification in machine-assisted medical decision making |
13 |
| Clustering single-cell RNA-seq data with a model-based deep learning approach |
11 |
| Feedback GAN for DNA optimizes protein functions |
11 |
| Evaluation of deep learning in non-coding RNA classification |
11 |
| Evolving embodied intelligence from materials to machines |
10 |
| Training deep neural networks for binary communication with the Whetstone method |
10 |
| An integrated iterative annotation technique for easing neural network training in medical image analysis |
10 |
| Automated de novo molecular design by hybrid machine intelligence and rule-driven chemical synthesis |
10 |
| Homeostasis and soft robotics in the design of feeling machines |
9 |
| The evolution of citation graphs in artificial intelligence research |
9 |
| Causal deconvolution by algorithmic generative models |
8 |
| Hopes and fears for intelligent machines in fiction and reality |
8 |
| Shared human-robot proportional control of a dexterous myoelectric prosthesis |
8 |
| Prediction of drug combination effects with a minimal set of experiments |
8 |
| Behavioural evidence for a transparency-efficiency tradeoff in human-machine cooperation |
8 |
| Human action recognition with a large-scale brain-inspired photonic computer |
8 |
| Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks |
7 |
| Predicting disease-associated mutation of metal-binding sites in proteins using a deep learning approach |
7 |
| Differential game theory for versatile physical human-robot interaction |
7 |
| Solving the Rubik's cube with deep reinforcement learning and search |
6 |
| Distributed sensing for fluid disturbance compensation and motion control of intelligent robots |
6 |
| Clinically applicable deep learning framework for organs at risk delineation in CT images |
6 |
| Unsupervised data to content transformation with histogram-matching cycle-consistent generative adversarial networks |
5 |
| Autonomous functional movements in a tendon-driven limb via limited experience |
5 |
| Learnability can be undecidable |
4 |
| Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning |
4 |
| Trusting artificial intelligence in cybersecurity is a double-edged sword |
4 |
| Deep convolutional neural networks in the face of caricature |
3 |
| Developing the knowledge of number digits in a child-like robot |
3 |
| Automated abnormality detection in lower extremity radiographs using deep learning |
3 |
| Intelligent feature engineering and ontological mapping of brain tumour histomorphologies by deep learning |
3 |
| Developing a brain atlas through deep learning |
3 |
| Improved fragment sampling for ab initio protein structure prediction using deep neural networks |
3 |
| Robotic manipulation and the role of the task in the metric of success |
2 |
| Leveraging implicit knowledge in neural networks for functional dissection and engineering of proteins |
2 |
