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Found 8 papers, 0 papers with code
Cluster Flow: how a hierarchical clustering layer make allows deep-NNs more resilient to hacking, more human-like and easily implements relational reasoning
Mankind can even do this with objects they have never seen before.
Icospherical Chemical Objects (ICOs) allow for chemical data augmentation and maintain rotational, translation and permutation invariance
Dataset augmentation is a common way to deal with small datasets; Chemistry datasets are often small.
Shape is (almost) all!: Persistent homology features (PHFs) are an information rich input for efficient molecular machine learning
PHFs success despite losing a large amount of chemical detail highlights how much of chemistry can be simplified to topological shape.
Single Memristor Logic Gates: From NOT to a Full Adder
Memristors have been suggested as a novel route to neuromorphic computing based on the similarity between them and neurons (specifically synapses and ion pumps).
Evolving Spiking Networks with Variable Resistive Memories
Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution.
Does the D.C. Response of Memristors Allow Robotic Short-Term Memory and a Possible Route to Artificial Time Perception?
Time perception is essential for task switching, and in the mammalian brain appears alongside other processes.
Is Spiking Logic the Route to Memristor-Based Computers?
Memristors have been suggested as a novel route to neuromorphic computing based on the similarity between neurons (synapses and ion pumps) and memristors.
Connecting Spiking Neurons to a Spiking Memristor Network Changes the Memristor Dynamics
Memristors have been suggested as neuromorphic computing elements.
