Summary of Retrieval-augmented Score Distillation For Text-to-3d Generation, by Junyoung Seo et al.
Retrieval-Augmented Score Distillation for Text-to-3D Generationby Junyoung Seo, Susung Hong, Wooseok Jang, Inès Hyeonsu Kim,…
Summary of On the Development Of a Practical Bayesian Optimisation Algorithm For Expensive Experiments and Simulations with Changing Environmental Conditions, by Mike Diessner et al.
On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with…
Summary of Black-box Approximation and Optimization with Hierarchical Tucker Decomposition, by Gleb Ryzhakov et al.
Black-Box Approximation and Optimization with Hierarchical Tucker Decompositionby Gleb Ryzhakov, Andrei Chertkov, Artem Basharin, Ivan…
Summary of Representation Surgery For Multi-task Model Merging, by Enneng Yang and Li Shen and Zhenyi Wang and Guibing Guo and Xiaojun Chen and Xingwei Wang and Dacheng Tao
Representation Surgery for Multi-Task Model Mergingby Enneng Yang, Li Shen, Zhenyi Wang, Guibing Guo, Xiaojun…
Summary of Architectural Strategies For the Optimization Of Physics-informed Neural Networks, by Hemanth Saratchandran et al.
Architectural Strategies for the optimization of Physics-Informed Neural Networksby Hemanth Saratchandran, Shin-Fang Chng, Simon LuceyFirst…
Summary of Discounted Adaptive Online Learning: Towards Better Regularization, by Zhiyu Zhang et al.
Discounted Adaptive Online Learning: Towards Better Regularizationby Zhiyu Zhang, David Bombara, Heng YangFirst submitted to…
Summary of Glocal Hypergradient Estimation with Koopman Operator, by Ryuichiro Hataya and Yoshinobu Kawahara
Glocal Hypergradient Estimation with Koopman Operatorby Ryuichiro Hataya, Yoshinobu KawaharaFirst submitted to arxiv on: 5…
Summary of Standard Gaussian Process Is All You Need For High-dimensional Bayesian Optimization, by Zhitong Xu et al.
Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimizationby Zhitong Xu, Haitao Wang,…
Summary of Rethinking Optimization and Architecture For Tiny Language Models, by Yehui Tang et al.
Rethinking Optimization and Architecture for Tiny Language Modelsby Yehui Tang, Fangcheng Liu, Yunsheng Ni, Yuchuan…
Summary of Prosac: Provably Safe Certification For Machine Learning Models Under Adversarial Attacks, by Chen Feng et al.
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacksby Chen Feng, Ziquan Liu,…