Summary of Self-supervised Visual Preference Alignment, by Ke Zhu and Zheng Ge and Liang Zhao and Xiangyu Zhang
Self-Supervised Visual Preference Alignmentby Ke Zhu, Zheng Ge, Liang Zhao, Xiangyu ZhangFirst submitted to arxiv…
Self-Supervised Visual Preference Alignmentby Ke Zhu, Zheng Ge, Liang Zhao, Xiangyu ZhangFirst submitted to arxiv…
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstructionby Sinisa Stekovic, Stefan Ainetter, Mattia D'Urso,…
Awareness of uncertainty in classification using a multivariate model and multi-viewsby Alexey Kornaev, Elena Kornaeva,…
Multi-objective evolutionary GAN for tabular data synthesisby Nian Ran, Bahrul Ilmi Nasution, Claire Little, Richard…
OptiGrad: A Fair and more Efficient Price Elasticity Optimization via a Gradient Based Learningby Vincent…
EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learningby Yue Jiang, Zixin Guo, Hamed Rezazadegan Tavakoli,…
Machine learning-based optimization workflow of the homogeneity of spunbond nonwovens with human validationby Viny Saajan…
Integrating Marketing Channels into Quantile Transformation and Bayesian Optimization of Ensemble Kernels for Sales Prediction…
Coreset Selection for Object Detectionby Hojun Lee, Suyoung Kim, Junhoo Lee, Jaeyoung Yoo, Nojun KwakFirst…
BG-YOLO: A Bidirectional-Guided Method for Underwater Object Detectionby Jian Zhang, Ruiteng Zhang, Xinyue Yan, Xiting…