Summary of Aucseg: Auc-oriented Pixel-level Long-tail Semantic Segmentation, by Boyu Han et al.
AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentationby Boyu Han, Qianqian Xu, Zhiyong Yang, Shilong Bao, Peisong…
Summary of Identifiable Shared Component Analysis Of Unpaired Multimodal Mixtures, by Subash Timilsina et al.
Identifiable Shared Component Analysis of Unpaired Multimodal Mixturesby Subash Timilsina, Sagar Shrestha, Xiao FuFirst submitted…
Summary of Dual Cone Gradient Descent For Training Physics-informed Neural Networks, by Youngsik Hwang et al.
Dual Cone Gradient Descent for Training Physics-Informed Neural Networksby Youngsik Hwang, Dong-Young LimFirst submitted to…
Summary of Soar: Self-supervision Optimized Uav Action Recognition with Efficient Object-aware Pretraining, by Ruiqi Xian et al.
SOAR: Self-supervision Optimized UAV Action Recognition with Efficient Object-Aware Pretrainingby Ruiqi Xian, Xiyang Wu, Tianrui…
Summary of Using Dynamic Loss Weighting to Boost Improvements in Forecast Stability, by Daan Caljon et al.
Using dynamic loss weighting to boost improvements in forecast stabilityby Daan Caljon, Jeff Vercauteren, Simon…
Summary of Super Level Sets and Exponential Decay: a Synergistic Approach to Stable Neural Network Training, by Jatin Chaudhary et al.
Super Level Sets and Exponential Decay: A Synergistic Approach to Stable Neural Network Trainingby Jatin…
Summary of Demo2vec: Learning Region Embedding with Demographic Information, by Ya Wen et al.
Demo2Vec: Learning Region Embedding with Demographic Informationby Ya Wen, Yulun ZhouFirst submitted to arxiv on:…
Summary of Is All Learning (natural) Gradient Descent?, by Lucas Shoji et al.
Is All Learning (Natural) Gradient Descent?by Lucas Shoji, Kenta Suzuki, Leo KozachkovFirst submitted to arxiv…
Summary of Learning to Help: Training Models to Assist Legacy Devices, by Yu Wu et al.
Learning To Help: Training Models to Assist Legacy Devicesby Yu Wu, Anand SarwateFirst submitted to…
Summary of Training Neural Networks For Modularity Aids Interpretability, by Satvik Golechha et al.
Training Neural Networks for Modularity aids Interpretabilityby Satvik Golechha, Dylan Cope, Nandi SchootsFirst submitted to…