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Found 4 papers, 0 papers with code
Interpretable Word Embedding Contextualization
In this paper, we propose a method of calibrating a word embedding, so that the semantic it conveys becomes more relevant to the context.
Training a Probabilistic Graphical Model with Resistive Switching Electronic Synapses
Current large scale implementations of deep learning and data mining require thousands of processors, massive amounts of off-chip memory, and consume gigajoules of energy.
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.
Experimental Demonstration of Array-level Learning with Phase Change Synaptic Devices
We demonstrate, in hardware, that 2-D crossbar arrays of phase change synaptic devices can achieve associative learning and perform pattern recognition.
