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Found 4 papers, 0 papers with code
Supervised classification-based stock prediction and portfolio optimization
In this work, we apply machine learning techniques to address automated stock picking, while using a larger number of financial parameters for individual companies than the previous studies.
Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array
Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nanoscale memory devices as synaptic elements.
Device and System Level Design Considerations for Analog-Non-Volatile-Memory Based Neuromorphic Architectures
This paper gives an overview of recent progress in the brain inspired computing field with a focus on implementation using emerging memories as electronic synapses.
ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours
In this work, we conducted a comprehensive analysis on the AlphaFold training procedure based on Openfold, identified that inefficient communications and overhead-dominated computations were the key factors that prevented the AlphaFold training from effective scaling.
