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Found 6 papers, 3 papers with code
Benchmarking Neural Network Training Algorithms
In order to address these challenges, we introduce a new, competitive, time-to-result benchmark using multiple workloads running on fixed hardware, the AlgoPerf: Training Algorithms benchmark.
Detecting Out-of-Distribution Examples with In-distribution Examples and Gram Matrices
We find that characterizing activity patterns by Gram matrices and identifying anomalies in gram matrix values can yield high OOD detection rates.
Ranked #13 on
Out-of-Distribution Detection
on CIFAR-10 vs CIFAR-100
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Efficient CDF Approximations for Normalizing Flows
Instead, we build upon the diffeomorphic properties of normalizing flows and leverage the divergence theorem to estimate the CDF over a closed region in target space in terms of the flux across its \emph{boundary}, as induced by the normalizing flow.
Detecting Out-of-Distribution Examples with Gram Matrices
We find that characterizing activity patterns by Gram matrices and identifying anomalies in Gram matrix values can yield high OOD detection rates.
Musical Speech: A Transformer-based Composition Tool
In this paper, we propose a new compositional tool that will generate a musical outline of speech recorded/provided by the user for use as a musical building block in their compositions.
Test-Time Training for Depression Detection
Previous works on depression detection use datasets collected in similar environments to train and test the models.
