Top Quant Interview Questions Asked by Tower Research Capital
In this article, we will cover some of the most representative and challenging quant interview questions from these firms. We’ll walk through detailed solutions, explanations of all key concepts, and provide example code and formulas where appropriate.
Self-attention is a core mechanism in modern machine learning, especially in natural language processing models like Transformers. At its essence, self-attention allows a model to weigh the importance of different elements within a sequence when encoding a particular element of that sequence. It dynamically computes a weighted sum of all elements, where the weights (attention scores) are determined by learned similarity functions.
Given an input sequence of \( n \) elements represented as vectors:
