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Found 4 papers, 1 papers with code
Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning
The dynamic expansion architecture is becoming popular in class incremental learning, mainly due to its advantages in alleviating catastrophic forgetting.
Temporal Information Processing on Noisy Quantum Computers
The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems.
Software tools for quantum control: Improving quantum computer performance through noise and error suppression
Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers.
Quantum Physics
Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems
In this paper, we develop a theory of learning nonlinear input-output maps with fading memory by dissipative quantum systems, as a quantum counterpart of the theory of approximating such maps using classical dynamical systems.
