Nanoparticle synthesis assisted by machine learning
Many properties of nanoparticles are governed by their shape, size, polydispersity and
surface chemistry. To apply nanoparticles in chemical sensing, medical diagnostics …
surface chemistry. To apply nanoparticles in chemical sensing, medical diagnostics …
Deep learning and its application to LHC physics
D Guest, K Cranmer, D Whiteson - Annual Review of Nuclear …, 2018 - annualreviews.org
Machine learning has played an important role in the analysis of high-energy physics data
for decades. The emergence of deep learning in 2012 allowed for machine learning tools …
for decades. The emergence of deep learning in 2012 allowed for machine learning tools …
A race-track trapped-ion quantum processor
SA Moses, CH Baldwin, MS Allman, R Ancona… - Physical Review X, 2023 - APS
We describe and benchmark a new quantum charge-coupled device (QCCD) trapped-ion
quantum computer based on a linear trap with periodic boundary conditions, which …
quantum computer based on a linear trap with periodic boundary conditions, which …
SMAC3: A versatile Bayesian optimization package for hyperparameter optimization
Algorithm parameters, in particular hyperparameters of machine learning algorithms, can
substantially impact their performance. To support users in determining well-performing …
substantially impact their performance. To support users in determining well-performing …
MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …
involve many electronic control units connected through intravehicle networks (IVNs) to …
Accelerated hierarchical density based clustering
L McInnes, J Healy - 2017 IEEE international conference on …, 2017 - ieeexplore.ieee.org
We present an accelerated algorithm for hierarchical density based clustering. Our new
algorithm improves upon HDBSCAN*, which itself provided a significant qualitative …
algorithm improves upon HDBSCAN*, which itself provided a significant qualitative …
A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns
In cancer, the primary tumour's organ of origin and histopathology are the strongest
determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic …
determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic …
Estimating electric motor temperatures with deep residual machine learning
W Kirchgässner, O Wallscheid… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Most traction drive applications lack accurate temperature monitoring capabilities, ensuring
safe operation through expensive oversized motor designs. Classic thermal modeling …
safe operation through expensive oversized motor designs. Classic thermal modeling …
Calorimetry with deep learning: particle simulation and reconstruction for collider physics
D Belayneh, F Carminati, A Farbin… - The European Physical …, 2020 - Springer
Using detailed simulations of calorimeter showers as training data, we investigate the use of
deep learning algorithms for the simulation and reconstruction of single isolated particles …
deep learning algorithms for the simulation and reconstruction of single isolated particles …
Optimizing machine learning algorithms for landslide susceptibility mapping along the Karakoram Highway, Gilgit Baltistan, Pakistan: A comparative study of baseline …
Algorithms for machine learning have found extensive use in numerous fields and
applications. One important aspect of effectively utilizing these algorithms is tuning the …
applications. One important aspect of effectively utilizing these algorithms is tuning the …