Deep learning architectures like CNNs and Transformers have significantly advanced biological sequence modeling by capturing local and long-range dependencies. However, their application in biological ...

When compiling the sample code for examples/16_ampere_tensorop_conv2dfprop/ampere_tensorop_conv2dfprop.cu, it fails with the following error message. Any other ...

In honor of Saul Bass’s birthday this month, we’re taking a look at some of the greatest animated title sequences from live-action movies (the topic of great credits sequences in animated movies is a ...

MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from ...

Abstract: The Fast Fourier Transform (FFT)-based convolution is the most popular fast convolution algorithm. In past work, we developed the Discrete Hirschman Transform (DHT)-based convolution. When ...

Reasoning efficiently across extended sequences is a major difficulty in machine learning. Recently, convolutions have emerged as a critical primitive for sequence modeling, supporting ...

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Abstract: This paper proposes a method for modeling event sequences with ambiguous timestamps, a time-discounting convolution. Unlike in ordinary time series, time intervals are not constant, small ...