In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...
Thriving in an exponential world requires more than a better strategy. It demands quantum thinking, the shift from linear ...
In January I wrote a piece titled “ 5 Physics Equations Everyone Should Know .” Lots of you weighed in with your own ...
When you shine a flashlight into a glass of water, the beam bends. That simple observation, familiar since ancient times, ...
Abstract: The robustness of convolutional neural networks (CNNs) is vital to modern AI-driven systems. It can be quanti-fied by formal verification by providing a certified lower bound, within which ...
Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...
Curvature-Based Piecewise Linear Approximation Method of GELU Activation Function in Neural Networks
Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...
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