Summary of Cycle-configuration: a Novel Graph-theoretic Descriptor Set For Molecular Inference, by Bowen Song et al.
Cycle-Configuration: A Novel Graph-theoretic Descriptor Set for Molecular Inferenceby Bowen Song, Jianshen Zhu, Naveed Ahmed…
Summary of Uav-enhanced Combination to Application: Comprehensive Analysis and Benchmarking Of a Human Detection Dataset For Disaster Scenarios, by Ragib Amin Nihal et al.
UAV-Enhanced Combination to Application: Comprehensive Analysis and Benchmarking of a Human Detection Dataset for Disaster…
Summary of Advancing Molecular Machine (learned) Representations with Stereoelectronics-infused Molecular Graphs, by Daniil A. Boiko et al.
Advancing Molecular Machine (Learned) Representations with Stereoelectronics-Infused Molecular Graphsby Daniil A. Boiko, Thiago Reschützegger, Benjamin…
Summary of Inference with the Upper Confidence Bound Algorithm, by Koulik Khamaru and Cun-hui Zhang
Inference with the Upper Confidence Bound Algorithmby Koulik Khamaru, Cun-Hui ZhangFirst submitted to arxiv on:…
Summary of Transformer Explainer: Interactive Learning Of Text-generative Models, by Aeree Cho et al.
Transformer Explainer: Interactive Learning of Text-Generative Modelsby Aeree Cho, Grace C. Kim, Alexander Karpekov, Alec…
Summary of Distinguishing Chatbot From Human, by Gauri Anil Godghase and Rishit Agrawal and Tanush Obili and Mark Stamp
Distinguishing Chatbot from Humanby Gauri Anil Godghase, Rishit Agrawal, Tanush Obili, Mark StampFirst submitted to…
Summary of Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy, by Wei Huo et al.
Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacyby Wei Huo, Changxin Liu, Kemi Ding,…
Summary of Robustness Investigation Of Cross-validation Based Quality Measures For Model Assessment, by Thomas Most et al.
Robustness investigation of cross-validation based quality measures for model assessmentby Thomas Most, Lars Gräning, Sebastian…
Summary of Dive: Subgraph Disagreement For Graph Out-of-distribution Generalization, by Xin Sun et al.
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalizationby Xin Sun, Liang Wang, Qiang Liu, Shu Wu,…
Summary of Model-based Transfer Learning For Contextual Reinforcement Learning, by Jung-hoon Cho et al.
Model-Based Transfer Learning for Contextual Reinforcement Learningby Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy WuFirst…