Summary of Mcpnet: An Interpretable Classifier Via Multi-level Concept Prototypes, by Bor-shiun Wang et al.
MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypesby Bor-Shiun Wang, Chien-Yi Wang, Wei-Chen ChiuFirst submitted…
Summary of Towards Sim-to-real Industrial Parts Classification with Synthetic Dataset, by Xiaomeng Zhu et al.
Towards Sim-to-Real Industrial Parts Classification with Synthetic Datasetby Xiaomeng Zhu, Talha Bilal, Pär Mårtensson, Lars…
Summary of Sentiment Analysis and Random Forest to Classify Llm Versus Human Source Applied to Scientific Texts, by Javier J. Sanchez-medina
Sentiment analysis and random forest to classify LLM versus human source applied to Scientific Textsby…
Summary of Tslanet: Rethinking Transformers For Time Series Representation Learning, by Emadeldeen Eldele et al.
TSLANet: Rethinking Transformers for Time Series Representation Learningby Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min…
Summary of Combining Statistical Depth and Fermat Distance For Uncertainty Quantification, by Hai-vy Nguyen et al.
Combining Statistical Depth and Fermat Distance for Uncertainty Quantificationby Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi,…
Summary of Revisiting Feature Prediction For Learning Visual Representations From Video, by Adrien Bardes et al.
Revisiting Feature Prediction for Learning Visual Representations from Videoby Adrien Bardes, Quentin Garrido, Jean Ponce,…
Summary of Nc-ttt: a Noise Contrastive Approach For Test-time Training, by David Osowiechi and Gustavo A. Vargas Hakim and Mehrdad Noori and Milad Cheraghalikhani and Ali Bahri and Moslem Yazdanpanah and Ismail Ben Ayed and Christian Desrosiers
NC-TTT: A Noise Contrastive Approach for Test-Time Trainingby David Osowiechi, Gustavo A. Vargas Hakim, Mehrdad…
Summary of Graph Data Augmentation with Gromow-wasserstein Barycenters, by Andrea Ponti
Graph data augmentation with Gromow-Wasserstein Barycentersby Andrea PontiFirst submitted to arxiv on: 12 Apr 2024CategoriesMain:…
Summary of A Complexity Map Of Probabilistic Reasoning For Neurosymbolic Classification Techniques, by Arthur Ledaguenel et al.
A Complexity Map of Probabilistic Reasoning for Neurosymbolic Classification Techniquesby Arthur Ledaguenel, Céline Hudelot, Mostepha…
Summary of Fedauxhmtl: Federated Auxiliary Hard-parameter Sharing Multi-task Learning For Network Edge Traffic Classification, by Faisal Ahmed et al.
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classificationby Faisal Ahmed, Myungjin…