Abstract: Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of ...
Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...
In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...
A new study reveals that dual-atom catalysts behave in a fundamentally different way than scientists previously thought, challenging a long-standing model used to predict catalytic performance.
Abstract: Deep Reinforcement Learning (DRL) has gained significant attention for its ability to solve combinatorial optimization problems, including the Traveling Salesman Problem (TSP). While ...
Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...
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