This paper introduces two extensions to the popular PyTorch machine learning framework,
TorchDynamo and TorchInductor, which implement the torch. compile feature released in …

Flux is library for machine learning (ML), written using the numerical computing language
Julia (Bezanson et al. 2017). The package allows models to be written using Julia's simple …

TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for
hardware-accelerated machine learning, suitable for both interactive research and …

The software needs of scientists and engineers are growing and their programs are
becoming more compute-heavy and problem-specific. This has led to an influx of non-expert …

Bayesian Optimization (BO) has shown great promise for the global optimization of functions
that are expensive to evaluate, but despite many successes, standard approaches can …

Julia has been heralded as a potential successor to Python for scientific machine learning
and numerical computing, boasting ergonomic and performance improvements. Since …

arxiv:1904.08368v1 [cs.LG] 17 Apr 2019 Page 1 Relay: A High-Level IR for Deep Learning
JARED ROESCH, Unversity of Washington STEVEN LYUBOMIRSKY, Unversity of Washington …

TensorFlow. jl is a Julia (Bezanson, Edelman, Karpinski, & Shah, 2017) client library for the
TensorFlow deep-learning framework (Abadi et al., 2015),(Abadi et al., 2016). It allows users …

Like many groups considering the new programming language Julia, we faced the
challenge of accessing the algorithms that we develop in Julia from R. Therefore, we …

Machine learning is an important tool for analyzing high-dimension hyperspectral data;
however, existing software solutions are either closed-source or inextensible research …