A large team of researchers working with Google Inc. and affiliated with a host of institutions in the U.S., one in Germany and one in the Netherlands has implemented a quantum approximate ...
Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...
Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...
This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...
Variational quantum algorithms (VQAs) are constrained by a trade-off: deeper circuits can cover a larger reachable quantum states but suffer from barren plateaus, while shallow circuits remain ...
The Quantum Approximate Optimization Algorithm (QAOA) represents a leading framework for addressing combinatorial optimisation problems on near-term quantum devices. By alternating between a cost ...
In a new paper in Science Advances, researchers at JPMorgan Chase, the U.S. Department of Energy's (DOE) Argonne National Laboratory and Quantinuum have demonstrated clear evidence of a quantum ...
A new nested multi-time-scale stochastic approximation method eliminates ratio-induced bias in likelihood-free parameter ...
Title Workflow to apply the Uniform Manifold Approximation and Projection algorithm to compare streamflow dynamics in hydrologic catchments version 1.0.0 ...
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