Neural clustering based visual representation learning
We investigate a fundamental aspect of machine vision: the measurement of features by
revisiting clustering one of the most classic approaches in machine learning and data …
revisiting clustering one of the most classic approaches in machine learning and data …
Aca-net: Towards lightweight speaker verification using asymmetric cross attention
In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding
extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric …
extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric …
[PDF][PDF] Aligned Deep Learning as a Random Sampling Method
L Pedro - 2023 - openreview.net
We show that the alignment problem in deep learning can be separated in two: A) estimate
systematic uncertainties as in Engineering; B) new due to Big Data, how to randomly sample …
systematic uncertainties as in Engineering; B) new due to Big Data, how to randomly sample …
MM-Lego: Modular Biomedical Multimodal Models with Minimal Fine-Tuning
K Hemker, N Simidjievski, M Jamnik - arXiv preprint arXiv:2405.19950, 2024 - arxiv.org
Learning holistic computational representations in physical, chemical or biological systems
requires the ability to process information from different distributions and modalities within …
requires the ability to process information from different distributions and modalities within …