Summary of Dkl-kan: Scalable Deep Kernel Learning Using Kolmogorov-arnold Networks, by Shrenik Zinage et al.
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networksby Shrenik Zinage, Sudeepta Mondal, Soumalya SarkarFirst submitted…
Summary of Neurosem: a Hybrid Framework For Simulating Multiphysics Problems by Coupling Pinns and Spectral Elements, By Khemraj Shukla et al.
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elementsby Khemraj…
Summary of Towards An Integrated Performance Framework For Fire Science and Management Workflows, by H. Ahmed et al.
Towards an Integrated Performance Framework for Fire Science and Management Workflowsby H. Ahmed, R. Shende,…
Summary of Robust Box Prompt Based Sam For Medical Image Segmentation, by Yuhao Huang et al.
Robust Box Prompt based SAM for Medical Image Segmentationby Yuhao Huang, Xin Yang, Han Zhou,…
Summary of From Feature Importance to Natural Language Explanations Using Llms with Rag, by Sule Tekkesinoglu and Lars Kunze
From Feature Importance to Natural Language Explanations Using LLMs with RAGby Sule Tekkesinoglu, Lars KunzeFirst…
Summary of Lawllm: Law Large Language Model For the Us Legal System, by Dong Shu et al.
LawLLM: Law Large Language Model for the US Legal Systemby Dong Shu, Haoran Zhao, Xukun…
Summary of Improving Pinns by Algebraic Inclusion Of Boundary and Initial Conditions, By Mohan Ren et al.
Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditionsby Mohan Ren, Zhihao Fang, Keren…
Summary of Efficient Pareto Manifold Learning with Low-rank Structure, by Weiyu Chen et al.
Efficient Pareto Manifold Learning with Low-Rank Structureby Weiyu Chen, James T. KwokFirst submitted to arxiv…
Summary of Be Aware Of Overfitting by Hyperparameter Optimization!, By Igor V. Tetko et al.
Be aware of overfitting by hyperparameter optimization!by Igor V. Tetko, Ruud van Deursen, Guillaume GodinFirst…
Summary of Improved Bounds For Pure Private Agnostic Learning: Item-level and User-level Privacy, by Bo Li et al.
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacyby Bo Li, Wei Wang,…