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Found 5 papers, 1 papers with code
Training Algorithm Matters for the Performance of Neural Network Potential: A Case Study of Adam and the Kalman Filter Optimizers
Here we compare the performance of two popular training algorithms, the adaptive moment estimation algorithm (Adam) and the Extended Kalman Filter algorithm (EKF), using the Behler-Parrinello neural network (BPNN) and two publicly accessible datasets of liquid water [Proc.
Bootstrapping Weakly Supervised Segmentation-free Word Spotting through HMM-based Alignment
In this paper, we propose an approach that utilises transcripts without bounding box annotations to train segmentation-free query-by-string word spotting models, given a partially trained model.
Weakly supervised segmentation
Word Spotting In Handwritten Documents
Flash X-ray diffraction imaging in 3D: a proposed analysis pipeline
Modern Flash X-ray diffraction Imaging (FXI) acquires diffraction signals from single biomolecules at a high repetition rate from X-ray Free Electron Lasers (XFELs), easily obtaining millions of 2D diffraction patterns from a single experiment.
Assessing Uncertainties in X-ray Single-particle Three-dimensional reconstructions
These two-dimensional diffraction patterns can be practically reconstructed and retrieved down to a resolution of a few \angstrom.
CannyFS: Opportunistically Maximizing I/O Throughput Exploiting the Transactional Nature of Batch-Mode Data Processing
We introduce a user mode file system, CannyFS, that hides latency by assuming all I/O operations will succeed.
Operating Systems
