Deep Tree Tensor Networks

The paper introduces the Deep Tree Tensor Network (DTTN), a novel architecture that employs a tree-like tensor network topology to capture $2^L$-order multiplicative interactions through multilinear operations. DTTN utilizes multiple antisymmetric interaction modules (AIMs) and shows superior performance across various benchmarks compared to existing methods and state-of-the-art architectures. This advancement may enhance interpretability in tensor network research and offers a new approach for practitioners looking to leverage tensor networks in natural image recognition tasks.