Array programming with NumPy
Array programming provides a powerful, compact and expressive syntax for accessing,
manipulating and operating on data in vectors, matrices and higher-dimensional arrays …
manipulating and operating on data in vectors, matrices and higher-dimensional arrays …
On hyperparameter optimization of machine learning algorithms: Theory and practice
Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …
areas. To fit a machine learning model into different problems, its hyper-parameters must be …
The astropy project: sustaining and growing a community-oriented open-source project and the latest major release (v5. 0) of the core package
The Python programming language is a high-level, interpreted (as opposed to compiled)
programming language that has become an industry standard across many computational …
programming language that has become an industry standard across many computational …
Instant neural graphics primitives with a multiresolution hash encoding
Neural graphics primitives, parameterized by fully connected neural networks, can be costly
to train and evaluate. We reduce this cost with a versatile new input encoding that permits …
to train and evaluate. We reduce this cost with a versatile new input encoding that permits …
[HTML][HTML] Magnetic control of tokamak plasmas through deep reinforcement learning
Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a
promising path towards sustainable energy. A core challenge is to shape and maintain a …
promising path towards sustainable energy. A core challenge is to shape and maintain a …
Scaling deep learning for materials discovery
Novel functional materials enable fundamental breakthroughs across technological
applications from clean energy to information processing,,,,,,,,,–. From microchips to batteries …
applications from clean energy to information processing,,,,,,,,,–. From microchips to batteries …
Pytorch: An imperative style, high-performance deep learning library
Deep learning frameworks have often focused on either usability or speed, but not both.
PyTorch is a machine learning library that shows that these two goals are in fact compatible …
PyTorch is a machine learning library that shows that these two goals are in fact compatible …
Advances and open problems in federated learning
Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …
devices or whole organizations) collaboratively train a model under the orchestration of a …
Transformers: State-of-the-art natural language processing
Recent progress in natural language processing has been driven by advances in both
model architecture and model pretraining. Transformer architectures have facilitated …
model architecture and model pretraining. Transformer architectures have facilitated …
Searching for mobilenetv3
We present the next generation of MobileNets based on a combination of complementary
search techniques as well as a novel architecture design. MobileNetV3 is tuned to mobile …
search techniques as well as a novel architecture design. MobileNetV3 is tuned to mobile …