Summary of Uncertainties Of Latent Representations in Computer Vision, by Michael Kirchhof
Uncertainties of Latent Representations in Computer Visionby Michael KirchhofFirst submitted to arxiv on: 26 Aug…
Summary of Llm-3d Print: Large Language Models to Monitor and Control 3d Printing, by Yayati Jadhav et al.
LLM-3D Print: Large Language Models To Monitor and Control 3D Printingby Yayati Jadhav, Peter Pak,…
Summary of Rethinking Knowledge Transfer in Learning Using Privileged Information, by Danil Provodin et al.
Rethinking Knowledge Transfer in Learning Using Privileged Informationby Danil Provodin, Bram van den Akker, Christina…
Summary of Function-space Mcmc For Bayesian Wide Neural Networks, by Lucia Pezzetti et al.
Function-Space MCMC for Bayesian Wide Neural Networksby Lucia Pezzetti, Stefano Favaro, Stefano PeluchettiFirst submitted to…
Summary of Streamline Tractography Of the Fetal Brain in Utero with Machine Learning, by Weide Liu et al.
Streamline tractography of the fetal brain in utero with machine learningby Weide Liu, Camilo Calixto,…
Summary of One-layer Transformers Fail to Solve the Induction Heads Task, by Clayton Sanford and Daniel Hsu and Matus Telgarsky
One-layer transformers fail to solve the induction heads taskby Clayton Sanford, Daniel Hsu, Matus TelgarskyFirst…
Summary of Automated Machine Learning in Insurance, by Panyi Dong et al.
Automated Machine Learning in Insuranceby Panyi Dong, Zhiyu QuanFirst submitted to arxiv on: 26 Aug…
Summary of Assessing Contamination in Large Language Models: Introducing the Logprober Method, by Nicolas Yax and Pierre-yves Oudeyer and Stefano Palminteri
Assessing Contamination in Large Language Models: Introducing the LogProber methodby Nicolas Yax, Pierre-Yves Oudeyer, Stefano…
Summary of An Embedding Is Worth a Thousand Noisy Labels, by Francesco Di Salvo and Sebastian Doerrich and Ines Rieger and Christian Ledig
An Embedding is Worth a Thousand Noisy Labelsby Francesco Di Salvo, Sebastian Doerrich, Ines Rieger,…
Summary of Exploiting Conjugate Label Information For Multi-instance Partial-label Learning, by Wei Tang et al.
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learningby Wei Tang, Weijia Zhang, Min-Ling ZhangFirst submitted…