Summary of Efficient Hyperparameter Importance Assessment For Cnns, by Ruinan Wang et al.
Efficient Hyperparameter Importance Assessment for CNNsby Ruinan Wang, Ian Nabney, Mohammad GolbabaeeFirst submitted to arxiv…
Efficient Hyperparameter Importance Assessment for CNNsby Ruinan Wang, Ian Nabney, Mohammad GolbabaeeFirst submitted to arxiv…
An Overview of Prototype Formulations for Interpretable Deep Learningby Maximilian Xiling Li, Korbinian Franz Rudolf,…
Meta-Transfer Learning Empowered Temporal Graph Networks for Cross-City Real Estate Appraisalby Weijia Zhang, Jindong Han,…
Multi-Source Temporal Attention Network for Precipitation Nowcastingby Rafael Pablos Sarabia, Joachim Nyborg, Morten Birk, Jeppe…
Carefully Structured Compression: Efficiently Managing StarCraft II Databy Bryce Ferenczi, Rhys Newbury, Michael Burke, Tom…
Bilinear MLPs enable weight-based mechanistic interpretabilityby Michael T. Pearce, Thomas Dooms, Alice Rigg, Jose M.…
Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamicsby Josiah C. Kratz, Jacob AdamczykFirst submitted…
Towards Foundation Models for Mixed Integer Linear Programmingby Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy…
A Framework to Enable Algorithmic Design Choice Exploration in DNNsby Timothy L. Cronin IV, Sanmukh…
Physics and Deep Learning in Computational Wave Imagingby Youzuo Lin, Shihang Feng, James Theiler, Yinpeng…