Summary of Sequential Choice in Ordered Bundles, by Rajeev Kohli et al.
Sequential choice in ordered bundlesby Rajeev Kohli, Kriste Krstovski, Hengyu Kuang, Hengxu LinFirst submitted to…
Summary of On the Role Of Depth and Looping For In-context Learning with Task Diversity, by Khashayar Gatmiry et al.
On the Role of Depth and Looping for In-Context Learning with Task Diversityby Khashayar Gatmiry,…
Summary of Linformer: a Linear-based Lightweight Transformer Architecture For Time-aware Mimo Channel Prediction, by Yanliang Jin et al.
LinFormer: A Linear-based Lightweight Transformer Architecture For Time-Aware MIMO Channel Predictionby Yanliang Jin, Yifan Wu,…
Summary of A Temporal Linear Network For Time Series Forecasting, by Remi Genet and Hugo Inzirillo
A Temporal Linear Network for Time Series Forecastingby Remi Genet, Hugo InzirilloFirst submitted to arxiv…
Summary of Reconstructing Dynamics From Sparse Observations with No Training on Target System, by Zheng-meng Zhai et al.
Reconstructing dynamics from sparse observations with no training on target systemby Zheng-Meng Zhai, Jun-Yin Huang,…
Summary of Deep Learning For Medical Text Processing: Bert Model Fine-tuning and Comparative Study, by Jiacheng Hu et al.
Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Studyby Jiacheng Hu, Yiru…
Summary of Tabdiff: a Mixed-type Diffusion Model For Tabular Data Generation, by Juntong Shi et al.
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generationby Juntong Shi, Minkai Xu, Harper Hua,…
Summary of Deep Learning-driven Microstructure Characterization and Vickers Hardness Prediction Of Mg-gd Alloys, by Lu Wang et al.
Deep Learning-Driven Microstructure Characterization and Vickers Hardness Prediction of Mg-Gd Alloysby Lu Wang, Hongchan Chen,…
Summary of Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss, by Kunal Dahiya et al.
Prototypical Extreme Multi-label Classification with a Dynamic Margin Lossby Kunal Dahiya, Diego Ortego, David JiménezFirst…
Summary of Teaformers: Tensor-augmented Transformers For Multi-dimensional Time Series Forecasting, by Linghang Kong et al.
TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecastingby Linghang Kong, Elynn Chen, Yuzhou Chen, Yuefeng…